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| author | elioat <elioat@tilde.institute> | 2023-08-23 07:52:19 -0400 |
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| committer | elioat <elioat@tilde.institute> | 2023-08-23 07:52:19 -0400 |
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| tree | 7d3305c1252c043bfe246ccc7deff0056aa6b5ab /js/games/nluqo.github.io/~bh/v3ch2 | |
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| download | tour-562a9a52d599d9a05f871404050968a5fd282640.tar.gz | |
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b/js/games/nluqo.github.io/~bh/v3ch2/grid5.gif new file mode 100644 index 0000000..dd41bd9 --- /dev/null +++ b/js/games/nluqo.github.io/~bh/v3ch2/grid5.gif Binary files differdiff --git a/js/games/nluqo.github.io/~bh/v3ch2/half-adder.gif b/js/games/nluqo.github.io/~bh/v3ch2/half-adder.gif new file mode 100644 index 0000000..e18e60a --- /dev/null +++ b/js/games/nluqo.github.io/~bh/v3ch2/half-adder.gif Binary files differdiff --git a/js/games/nluqo.github.io/~bh/v3ch2/math.html b/js/games/nluqo.github.io/~bh/v3ch2/math.html new file mode 100644 index 0000000..194753f --- /dev/null +++ b/js/games/nluqo.github.io/~bh/v3ch2/math.html @@ -0,0 +1,2870 @@ +<HTML> +<HEAD> +<TITLE>Computer Science Logo Style vol 3 ch 2: Discrete Mathematics</TITLE> +</HEAD> +<BODY> +<CITE>Computer Science Logo Style</CITE> volume 3: +<CITE>Beyond Programming</CITE> 2/e Copyright (C) 1997 MIT +<H1>Discrete Mathematics</H1> + +<TABLE width="100%"><TR><TD> +<IMG SRC="../csls3.jpg" ALT="cover photo"> +<TD><TABLE> +<TR><TD align="right"><CITE><A HREF="http://www.cs.berkeley.edu/~bh/">Brian +Harvey</A><BR>University of California, Berkeley</CITE> +<TR><TD align="right"><BR> +<TR><TD align="right"><A HREF="../pdf/v3ch02.pdf">Download PDF version</A> +<TR><TD align="right"><A HREF="../v3-toc2.html">Back to Table of Contents</A> +<TR><TD align="right"><A HREF="../v3ch1/v3ch1.html"><STRONG>BACK</STRONG></A> +chapter thread <A HREF="../v3ch3/v3ch3.html"><STRONG>NEXT</STRONG></A> +<TR><TD align="right"><A HREF="https://mitpress.mit.edu/books/computer-science-logo-style-second-edition-volume-3">MIT +Press web page for <CITE>Computer Science Logo Style</CITE></A> +</TABLE></TABLE> + +<HR><P>Program file for this chapter: <A HREF="math.lg"><CODE>math</CODE></A> + + + +<P>Computer scientists often use mathematics as a tool in their work, but the +mathematical problems that arise in computer science are of a special kind. +Consider these examples: + +<P>Suppose you have a nondeterministic FSM with five states and you want to +convert it to a deterministic one. What is the largest number of states +that might be required for the new machine? Well, each state of the new +machine corresponds to some <EM>combination</EM> of states of the old one, +because the conversion works by finding multiple transitions (from some state +via the same input character to multiple states) and creating a new state +that combines all those resulting states. How many such combinations are +possible? In other words, how many <EM>subsets</EM> does a five-element set +have? The answer is 2<SUP><SMALL>5</SMALL></SUP> or 32 states. (31, really, because one of those +is the empty subset and that will never be used.) + +<P>Suppose you want to write a program to translate telephone numbers into +letters. A telephone number has seven digits, each of which corresponds to +three letters. How many different strings of letters are possible? Well, +there are three choices for the first digit, times three for the second, and +so on... + +<P>These are typical of the kinds of mathematics problems that a computer + +scientist confronts in that they are <EM>counting</EM> problems--ones that +involve integers. Another relevant kind of problem is the <EM>logic</EM> +problem, in which the values under consideration are just <CODE>true</CODE> and +<CODE>false</CODE>. These areas of mathematics are quite different from what is +studied in the usual high school and college math courses: algebra, +geometry, trig, calculus, differential equations. Those courses deal with +<EM>measurement</EM> problems, in which the answer can be any number, +including a fraction or an irrational number. This conventional mathematics + +curriculum, studying <EM>continuous</EM> functions, is dictated by the needs +of physics and the physics-based engineering subjects. Computer scientists +need a different kind of math, called <EM>discrete</EM> mathematics. +("Discrete" is the opposite of "continuous" and is not the same word as +its homonym "discreet" meaning tactful.) + +<P><H2>Propositional Logic</H2> + +<P>You already know that what in Logo is called an <EM>operation</EM> is the +computer programming version of a mathematical <EM>function.</EM> The inputs +and outputs of Logo operations may be numbers, or they may be other kinds of +words or lists. In ordinary algebra the functions we use have numeric +values. Certain Logo operations are identical to the ones used in algebra: +<CODE>sin :x</CODE> is sin(<EM>x</EM>) and <CODE>sqrt :x</CODE> is √<EM>x</EM>. On the other +hand, there is nothing in ordinary school mathematics quite like <CODE>first</CODE> +or <CODE>sentence</CODE>. You may have been taught to use the word "function" +only when you see a notation like <EM>f</EM>(<EM>x</EM>), but in fact the ordinary +arithmetic operations are functions, too. The addition in <EM>a</EM>+<EM>b</EM> is a +function with two arguments, just like <CODE>sum :a :b</CODE> in Logo. + +<P> + +<P>In Logo there are also operations whose inputs and outputs are the words +<CODE>true</CODE> and <CODE>false</CODE>. The primitive operations in this category are +<CODE>and</CODE>, <CODE>or</CODE>, and <CODE>not</CODE>. Just as algebra deals with numeric +functions, <EM>logic</EM> is the branch of mathematics that deals with these + +<EM>truth-valued</EM> functions. Instead of numbers, these functions combine +<EM>propositions</EM>: statements that may be true or false. A Logo +expression like <CODE>:x=0</CODE> represents a proposition. "Abraham Lincoln was +the King of England" is a proposition; it happens to be false, but it's a +perfectly valid one because it asserts something that's either true or +false. "It will rain in Boston tomorrow" is a proposition whose truth +value we don't know yet. "Chinese food is better than French food" is an +example of a sentence whose validity as a proposition is open to question. +If I say that, I'm expressing my personal taste, not an objective statement +that could be proven true or false.<SUP>*</SUP> + +<P><SMALL><BLOCKQUOTE><SMALL><SUP>*</SUP>On the other hand, "The +Beatles are better than Led Zeppelin" is a perfectly valid, obviously true +proposition.</SMALL></BLOCKQUOTE></SMALL><P>Logical functions combine <EM>simple</EM> propositions into <EM>compound</EM> +propositions. For example, "Either Abraham Lincoln was the King of England +or he was the President of the United States" is a +compound proposition. +It's true even though one of the simple propositions within it is false. +Just as in algebra we use letters like <EM>x</EM> to represent numbers and +expressions like <EM>x</EM>+<EM>y</EM> to indicate the use of functions to combine numbers, +in logic we use letters to represent propositions and there are function +symbols for the logical functions. If <EM>p</EM> is the proposition "Abraham +Lincoln was the King of England," and <EM>q</EM> is the proposition "Abraham +Lincoln was the President of the United States," then the expression <EM>p</EM>∨<EM>q</EM> represents the compound proposition above. The symbol ∨ represents +the <EM>or</EM> function; ∧ +represents <EM>and</EM>; ¬ and ∼ +are alternative representations for <EM>not.</EM> The symbol → represents +"implies"; it turns out that <EM>p</EM>→<EM>q</EM> is equivalent to ¬<EM>p</EM>∨<EM>q</EM>; +in other words, the value of the function is true if either the "if" part +is <EM>false</EM> or the "then" part is true. An example of the former is +the classic "If wishes were horses then beggars would ride." + +<P>(Don't confuse the → function with the Logo <CODE>if</CODE> command. The +latter isn't a function (an operation), but a command. It tells Logo to +take some <EM>action</EM> if a given condition is met. The operation + +<P><PRE>to implies :p :q +output or (not :p) :q +end +</PRE> + +<P>is the Logo equivalent of the → function in logic.) + +<P>The most important use of logic in mathematics is in understanding the idea +of <EM>proof.</EM> What is a valid reason for claiming that some proposition +has been proven true? Many people come across the idea of proof for the +first and last time in high school geometry. We are asked to prove some +proposition like "the sum of the interior angles of a triangle is +180°." For each step in the proof we must give a <EM>reason</EM> +such as "things equal to the same thing are equal to each other." + +<P>In logic there are certain rules that allow us to infer one proposition from +one or more previously known propositions. These rules correspond +roughly to the "reasons" in a geometry proof. They are called +<EM>rules of inference.</EM> You use rules of +inference informally all the time, whenever +you try to convince someone of something by reasoning. "Is Jay here?" +"Yes." "How do you know?" "I saw his car in the driveway, and if his car +is here, he must be here too." + +<P>Suppose we use the letter <EM>p</EM> to represent the proposition "Jay's car is +here" and the letter <EM>q</EM> to represent "Jay is here." Then the reasoning +quoted in the last paragraph says "<EM>p</EM> is true and <EM>p</EM>→<EM>q</EM> is true, so +<EM>q</EM> must be true." ("<EM>p</EM>→<EM>q</EM>" is the proposition "If Jay's car is +here, he must be here too.") The fact that <EM>p</EM> and <EM>p</EM>→<EM>q</EM> allow us to +infer <EM>q</EM> is a rule of inference. (Of course the rule doesn't +tell us about the truth of its component propositions. We have to determine +that by some means outside of logic, such as observation of the world. +I had to <EM>see</EM> Jay's car in the driveway to know that <EM>p</EM> is true.) + +<P><H2>An Inference System</H2> + +<P>What does all this have to do with computer science? One application of +logic is in <EM>inference systems</EM>: programs that deduce propositions +from other ones. Such systems are important both in business applications +where large data bases are used and in artificial intelligence programs that +try to answer questions based on information implied by some text but not +explicit in the text. + +<P>In this section I'll show you a special-purpose inference system that solves +logic problems. Logic problems are the ones in which you're given +certain propositions and asked to deduce others. Mr. Smith lives next to +the carpenter; John likes classical music; who lives in the yellow house? +Here is a typical problem taken from <EM>Mind Benders,</EM> Book B-2, +by Anita Harnadek. + +<P><BLOCKQUOTE> +<P><A NAME="harnadek">A cub reporter +interviewed four people. He was very careless, however. +Each statement he wrote was half right and half wrong. He went back and +interviewed the people again. And again, each statement he wrote was half +right and half wrong. From the information below, can you straighten out +the mess? + +<P>The first names were Jane, Larry, Opal, and Perry. The last names were +Irving, King, Mendle, and Nathan. The ages were 32, 38, 45, and 55. The +occupations were drafter, pilot, police sergeant, and test car driver. + +<P>On the first interview, he wrote these statements, one from each person: + +<P><P> + +<P><TABLE><TR><TH align="right" valign="top">1.<TD> <TD valign="top"> Jane: "My name is Irving, and I'm 45." +<TR><TH align="right" valign="top">2.<TD> <TD valign="top"> King: "I'm Perry and I drive test cars." +<TR><TH align="right" valign="top">3.<TD> <TD valign="top"> Larry: "I'm a police sergeant and I'm 45." +<TR><TH align="right" valign="top">4.<TD> <TD valign="top"> Nathan: "I'm a drafter, and I'm 38." + +<P></TABLE> + +<P>On the second interview, he wrote these statements, one from each person: + +<P><P> + +<P><TABLE><TR><TH align="right" valign="top">5.<TD> <TD valign="top"> Mendle: "I'm a pilot, and my name is Larry." +<TR><TH align="right" valign="top">6.<TD> <TD valign="top"> Jane: "I'm a pilot, and I'm 45." +<TR><TH align="right" valign="top">7.<TD> <TD valign="top"> Opal: "I'm 55 and I drive test cars." +<TR><TH align="right" valign="top">8.<TD> <TD valign="top"> Nathan: "I'm 38 and I drive test cars." + +<P></TABLE></BLOCKQUOTE> + +<P> +<CENTER><IMG SRC="grid.gif" ALT="figure: grid"></CENTER> + + +<P>The chart provided with the problem is a guide to its solution. Each square +in the chart represents a proposition. For example, the box where the +"Larry" row meets the "pilot" column represents the proposition "Larry +is the pilot." In solving the problem, you can put marks in the boxes to +indicate what you know about the propositions. The status of a proposition +need not be only true or false. Initially the status of each proposition is +<EM>unknown</EM>; we have no idea whether it's true or false. The structure +of this particular problem also allows the status of a proposition to be that +it is linked with another proposition in an <EM>exclusive-or</EM> +relationship; that is, if one of the linked propositions turns out to be +true, then the other must be false, and vice versa. You can use whatever +notation you find convenient to express these possibilities. After +experimenting with T and F and with check marks and crosses, I found that +circles for true propositions and crosses for false ones made it easiest for +me to see quickly the pattern of known truths. For the linked propositions, +I used the statement numbers (1 to 8) in the boxes; two boxes with the same +number represent linked statements. + +<P>You should probably solve this problem by hand before we go on to discuss +the computer solution. Stop reading now and work on the problem if you want +to do it without any hints from me. + +<P>Let me introduce a little new terminology to help in the following +discussion. I'll call something like "last name" or "occupation" a +<EM>category</EM>; something like "Mendle" or "pilot" I'll call an +<EM>individual.</EM> As I'm using this terminology, "Mendle" and "pilot" +are two different individuals even if they turn out, when we solve the +problem, to be the same person. + +<P>It's important that each group of four statements contains one from each +person, because the names of the speakers include first and last names. +That is, from the first group of statements we know that Jane, King, Larry, +and Nathan are four distinct people. This falsifies such propositions as +"Jane is King." After noting the first group of statements my chart looks +like this: + +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/grid2.gif" ALT="figure: grid2"></CENTER> + +<P>From the second group of statements we learn that Mendle, Jane, Opal, and +Nathan are all distinct people. When I marked an X in the "Jane is +Mendle" box, I noticed that all but one last name for Jane had been +eliminated. I therefore put a circle in the "Jane is Irving" box. This +illustrates a special rule of inference for problems of this kind: If, for +a given individual <EM>x</EM>, all but one proposition "<EM>x</EM> is <EM>y</EM>" have been +falsified for a certain <EM>category</EM> of <EM>y</EM> individuals, then the +remaining proposition in that category must be true. (The reason I'm going +through this analysis is that the rules of inference I discover while +working the problem by hand are going to end up in the design of the +computer program.) I'm going to call this the <EM>elimination</EM> rule. + + +<P>Since Jane is Irving, nobody else can be Irving. This falsifies three +propositions whose status was formerly unknown: "Larry is Irving," +"Opal is Irving," and "Perry is Irving." (The truth of "Jane is Irving" +would also falsify "Jane is King" and so on, but we already knew those to +be false.) The general rule is that if "<EM>x</EM> is <EM>y</EM>" is true then "<EM>x</EM> is +<EM>z</EM>" must be false for all other <EM>z</EM> in the same category as <EM>y</EM>, and +likewise "<EM>w</EM> is <EM>y</EM>" is false for all other <EM>w</EM> in the same category as +<EM>x</EM>. I'll call this the <EM>uniqueness</EM> rule. + + +<P>The proposition "Jane is Irving" was linked with the proposition +"Jane is 45" earlier. That latter proposition must therefore be false. +This is another rule of inference, the <EM>link falsification</EM> rule. +There is also a <EM>link verification</EM> rule that comes into play when a +linked proposition is found to be false; the other linked proposition must +then be true. + +<P>Since we know that "Jane is 45" is false, and that "Jane is Irving" is +true, it follows that "Irving is 45" must be false. The general rule is +that if "<EM>x</EM> is <EM>y</EM>" is true and "<EM>x</EM> is <EM>z</EM>" is false, then "<EM>y</EM> is +<EM>z</EM>" must also be false. Similarly, if "<EM>x</EM> is <EM>y</EM>" is true and "<EM>x</EM> is +<EM>z</EM>" is true, then "<EM>y</EM> is <EM>z</EM>" must be true. I'll call these the +<EM>transitive</EM> rules. + + +<P>You should be following along with your own copy of the chart. By the +elimination rule, "Opal is King" must be true. Then, by the uniqueness +rule, "Perry is King" is false. Then, by the link verification rule, +"King is test driver" must be true. By the transitive rule, "Opal is +test driver" is true also. Here is my chart after making all possible +deductions from the fact that Mendle, Jane, Opal, and Nathan are distinct +people: + +<P><CENTER><IMG SRC="grid3.gif" ALT="figure: grid3"></CENTER> + +<P>Looking at statement number 5, we see that "Mendle is pilot" is linked to +"Mendle is Larry." But we already know that the latter is true, so the +former must be false. We can just put an X in that box and not bother +marking the number 5 anywhere. The same is true for statements 6 and 7; +here's my chart after statement 7: + +<P> +<CENTER><IMG SRC="grid4.gif" ALT="figure: grid4"></CENTER> + +<P>I haven't marked anything in the +age vs. occupation section of the chart, even though I can deduce some +propositions for that section. For example, I know that "Jane is pilot" +is true and that "Jane is 45" is false. By the transitive rule, "pilot +is 45" must be false. I just haven't bothered making <EM>all</EM> possible +deductions; I can always fill in that section of the chart if I get to the +end of the problem and still don't know who's who. + +<P>Before dealing with the final statement we know all the pairings of first +and last names, but we don't know any ages and we only know half the jobs. +The last statement lets loose a flurry of deductions. The critical one is +that if Nathan is 38, he or she (Perry is an ambiguous first name) can't be +the drafter because of the link from statement 4. Here is my final chart: + +<P><CENTER><IMG SRC="grid5.gif" ALT="figure: grid5"></CENTER> + +<P>Once it was clear that I was in the final steps of the solution, I +didn't bother maintaining the age vs. last name section. The results can +be found by reading just the three sections at the top; for example, +Jane is Irving, the pilot, and 55. + +<P><H2>Problems with Ordering</H2> + +<P>The elimination, uniqueness, and transitive rules are useful in just about +all logic problems, but the link falsification and link verification rules +depend on this specific problem's gimmick that we are given pairs of +propositions and told that exactly one of them is true. To solve other +problems, a more flexible kind of linkage is needed; we must be able to say +"if <EM>p</EM> is true, then <EM>q</EM> is true also" or "if <EM>p</EM> is false, then <EM>q</EM> +must be true," and so on. + +<P>A very common kind of linkage is an <EM>ordering,</EM> in which we are +told a sequence of events, or a row of houses on a street, for example. +In the cub reporter problem, the ages form an ordering, but aren't used +as such--that is, the problem doesn't include clues such as "the test +driver is younger than Jane." Suppose we did see that clue; what could +we conclude from it? Certain propositions would be settled for sure: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top">The test driver must not be Jane. +<TR><TH align="right" valign="top">•<TD> <TD valign="top">The test driver isn't the oldest age (55). +<TR><TH align="right" valign="top">•<TD> <TD valign="top">Jane isn't the youngest age (32). +</TABLE><P> + +<P>Other propositions would be linked by <EM>implications:</EM> + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Jane is 38, <STRONG>then</STRONG> the driver is 32. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Jane is 45, <STRONG>then</STRONG> the driver is 32 or 38. +</TABLE><P> + +<P>and so on. (Actually, the second of these isn't directly +representable on the chart, because there's no notation for a single +proposition with two alternatives, like "32 or 38." So instead +we'd represent this using propositions about what <EM>can't</EM> be +true: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Jane is 45, <STRONG>then</STRONG> the driver is not 55. +</TABLE><P> + +<P>We already know that the driver isn't Jane, so there's no need +to record the implication that if Jane is 45 the driver isn't 45.) + +<P>Here is another problem, called "Forgetful Footes," +by Diane C. Baldwin. +It is taken from <EM>The Dell Book of Logic Problems #4.</EM> + +<P><BLOCKQUOTE> + +<P><A NAME="baldwin">The forgetful Foote</A> family +fairly flew from their flat up Fleet Street +to the freeway for a fling in Florida. Before they passed five +intersections, Felix and the other four Footes found they each had forgotten +something (including the food) and were forced back to their flat to fetch +it. Each turnaround was made at a different street intersection, one of +them at Field Street. From the following clues, can you figure out who +forgot what and in what order, and find the order of the intersections on +Fleet Street from the Foote's flat to the freeway? + +<P><P> + +<P><TABLE><TR><TH align="right" valign="top">1.<TD> <TD valign="top"> The second turnaround began at the street following Flag Street and +the street before Fred had to return to the flat. +<TR><TH align="right" valign="top">2.<TD> <TD valign="top"> The men were responsible for the return for the film, the +turnaround at Fig Street, and the fifth trip back. +<TR><TH align="right" valign="top">3.<TD> <TD valign="top"> Fork Street followed the one where they returned to fetch the +flashlight and preceded the one where a woman had them make their first +turnaround. +<TR><TH align="right" valign="top">4.<TD> <TD valign="top"> The final trip back didn't begin at Frond Street, nor was it the +one to fetch the fan. +<TR><TH align="right" valign="top">5.<TD> <TD valign="top"> Frank's forgetfulness turned them back one block and one return +trip following Francine's. +<TR><TH align="right" valign="top">6.<TD> <TD valign="top"> One woman was the third to forget, while the other woman turned +them back at Flag Street. +<TR><TH align="right" valign="top">7.<TD> <TD valign="top"> They returned for the fiddle just before the trip back that began +at Frond Street and just following the one requested by Flo. + +<P></TABLE></BLOCKQUOTE><P> + +<P>This problem includes <EM>two</EM> orderings. The order of the intersections +with cross streets is not necessarily the same as the time order of the +return trips. That is, the Footes might have gone four blocks before making +their first turnaround, then gone only one block before the second return, +and so on. In making a chart for this problem, I used the numbers 1-5 to +represent the order of streets, and the ordinals 1st-5th to represent the +time order of return trips. Clue 1, then, gives us this series of +implications: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Flag Street is 1, <STRONG>then</STRONG> 2nd is 2. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Flag Street is 2, <STRONG>then</STRONG> 2nd is 3. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Flag Street is 3, <STRONG>then</STRONG> 2nd is 4. +<P> +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 2, <STRONG>then</STRONG> Flag Street is 1. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 3, <STRONG>then</STRONG> Flag Street is 2. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 4, <STRONG>then</STRONG> Flag Street is 3. +<P> +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 2, <STRONG>then</STRONG> Fred is 3. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 3, <STRONG>then</STRONG> Fred is 4. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 4, <STRONG>then</STRONG> Fred is 5. +<P> +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Fred is 3, <STRONG>then</STRONG> 2nd is 2. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Fred is 3, <STRONG>then</STRONG> 2nd is 3. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Fred is 5, <STRONG>then</STRONG> 2nd is 4. + +<P></TABLE><P> + +<P>It may seem that there are some missing from this list. What if +Flag Street is 4? But that can't happen (and I so marked the chart) because +then 2nd would have to be 5, and that would make Fred 6, which is too far. +But notice that we do have to include both directions of implication between +any two propositions. The clue tells us that if Flag Street is 1, then 2nd +is 2, and also that if 2nd is 2, then Flag Street is 1. + +<P>See if you can solve this problem, and then we'll talk about the +Logo-based inference system. + +<P><H2>Data Structure</H2> + +<P>In addition to the status of the "<EM>x</EM> is <EM>y</EM>" propositions, the program +needs to keep track of the categories, like "first name," and the +individuals within each category. This information is needed for the sake +of the elimination and uniqueness rules. I chose to have a global variable +named <CODE>categories</CODE> containing (for the cub reporter problem) the list + +<P><PRE>[first last age job] +</PRE> + +<P>Each of the elements of that list is the name of a variable +containing the individuals in that category; for example, <CODE>:age</CODE> is +the list + +<P><PRE>[32 38 45 55] +</PRE> + +<P>The status of the "is" propositions is kept in property lists associated +with the names of individuals. For example, to indicate that the proposition +"Jane is King" is false, the program carries out these two instructions: + +<P><PRE>pprop "Jane "King "false +pprop "King "Jane "false +</PRE> + +<P>Both are necessary because we can't predict whether we're going +to be figuring out something about Jane or something about King when we +next need this information. Actually, the fact that the proposition is +stored twice reflects another inference rule, one that's so obvious we +don't think about it at all when solving these problems without using a +computer: the <EM>symmetric</EM> rule says that if <EM>x</EM> is <EM>y</EM>, then +<EM>y</EM> is <EM>x</EM>. + +<P>If a given property's value is the empty list, that means that the truth of +the proposition is unknown. (Remember that Logo property lists give the +empty list as the value of a property that you haven't defined explicitly, +so I don't have to predefine all possible properties.) The word <CODE>true</CODE> +means that the proposition is known to be true; the word <CODE>false</CODE> means +that it's known to be false. If the proposition is linked to other +propositions by implication, then the value of the property is a list +containing four-element implication lists. The first member of each +implication is <CODE>true</CODE> or <CODE>false</CODE> to indicate which value of this +proposition implies something about the other proposition. The next two +members are names of individuals, indicating which other proposition is +determined by this one. The fourth member is again <CODE>true</CODE> or <CODE> +false</CODE>, indicating whether that other proposition is implied to be true +or implied to be false. + +<P>For example, the +statement "My name is Irving, and I'm 45" attributed to Jane is stored as +the following two implications: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top">Under <CODE>Jane</CODE> and <CODE>Irving</CODE>, the list <CODE>[true Jane 45 false]</CODE>. +<TR><TH align="right" valign="top">•<TD> <TD valign="top">Under <CODE>Jane</CODE> and <CODE>45</CODE>, the list <CODE>[true Jane Irving false]</CODE>. +</TABLE><P> + +<P>Although the data structure as described so far +contains all the necessary information, it +turned out to be convenient to include some redundant forms of the same +information. For example, the elimination rule and the uniqueness rule +require the program to find all the <EM>peers</EM> of an individual--the +other individuals in the same category. It would be possible to start with +<CODE>:categories</CODE> and search for the known individual in a category list, +but it was easier to give each individual a <CODE>category</CODE> property whose +value is the name of the category to which it belongs. + +<P>Similarly, the transitive rule needs to know all of the propositions +involving a particular individual that are known to be true, and all +those that are known to be false. This +information is implicit in the properties already described, but to simplify +the program each individual has a <CODE>true</CODE> property whose value is a list +of the other individuals known to be equal to this one, and a <CODE>false</CODE> +property whose value is a list of the others known to be different from +this one. For example, after +processing statement 7 we know that Jane is Irving and that Jane is the +pilot, but we don't know Jane's age. Therefore the property list for <CODE> +Jane</CODE> has a property whose name is <CODE>true</CODE> and whose value is the list + +<P><PRE>[Irving pilot] +</PRE> + +<P>and one whose name is <CODE>false</CODE> and whose value is + +<P><PRE>[King Mendle Nathan drafter sergeant driver] + +</PRE> + +<P>Finally, it turned out that at the end of the program, in order to print out +the solutions, it was convenient to have, for each individual, properties +with a category as the name and an individual in that category as the value. +For example, since Jane's last name is Irving, <CODE>Jane</CODE> has a property +whose name is <CODE>last</CODE> and whose value is <CODE>Irving</CODE>. + +<P><H2>Program Structure: Recording Simple Propositions</H2> + +<P>I wanted to enter the problem as a series of assertions, each represented by +a Logo instruction. That is, I wrote this procedure: + +<P><PRE>to cub.reporter +cleanup +category "first [Jane Larry Opal Perry] +category "last [Irving King Mendle Nathan] +category "age [32 38 45 55] +category "job [drafter pilot sergeant driver] +differ [Jane King Larry Nathan] +says "Jane "Irving 45 +says "King "Perry "driver +says "Larry "sergeant 45 +says "Nathan "drafter 38 +differ [Mendle Jane Opal Nathan] +says "Mendle "pilot "Larry +says "Jane "pilot 45 +says "Opal 55 "driver +says "Nathan 38 "driver +print [] +solution +end +</PRE> + +<P>(The first instruction erases any old property lists left over +from a previous logic problem; the last prints out the results.) I made <CODE> +category</CODE>, <CODE>differ</CODE>, and <CODE>says</CODE> print out their inputs when invoked, +so that you can watch the progress of the solution while it's being computed. + +<P>The procedures <CODE>differ</CODE> and <CODE>says</CODE> were designed to reflect the +terms in which this problem is presented, rather than the internal workings +of the inference system. That is, if you compare the problem statement with +this procedure, it's easy to see which instructions represent which clues, +even if you have no idea how the program will actually solve the problem! +Our task is to implement <CODE>differ</CODE> and <CODE>says</CODE> using propositional +logic. + +<P>There's an important difference between <CODE>differ</CODE> and <CODE>says</CODE>. <CODE> +Differ</CODE> gives us direct information about the truth or falsehood of some +simple propositions; specifically, we learn that several "<EM>x</EM> is <EM>y</EM>" +propositions are false. <CODE>Says</CODE>, on the other hand, gives us no +direct information about simple propositions; it tells us about +implications linking two such propositions. + +<P>First let's consider how <CODE>differ</CODE> works. The instruction + +<P> + +<P><PRE>differ [Jane King Larry Nathan] +</PRE> + +<P>tells us that Jane is not King, Jane is not Larry, Jane is +not Nathan, King is not Larry, King is not Nathan, and Larry is not Nathan. +In effect, <CODE>differ</CODE> will carry out the instructions + +<P><PRE>falsify "Jane "King +falsify "Jane "Larry +falsify "Jane "Nathan +falsify "King "Larry +falsify "King "Nathan +falsify "Larry "Nathan +</PRE> + +<P>There's no need to invoke <CODE>falsify</CODE> for the six cases with +inputs in the opposite order (such as the proposition that King is not Jane) +because, as we'll see, <CODE>falsify</CODE> knows about the symmetric rule and +will record those automatically. By the way, some of these six are +unnecessary because the two individuals have the same category and therefore +couldn't possibly be the same, such as Jane and Larry, both first names. +But <CODE>falsify</CODE> will catch these cases and return without doing anything. + +<P>Here's how <CODE>differ</CODE> actually carries out all those <CODE>falsify</CODE> +instructions: + +<P><PRE>to differ :list +print (list "differ :list) +foreach :list [differ1 ? ?rest] +end + +to differ1 :a :them +foreach :them [falsify :a ?] +end +</PRE> + +<P><CODE>Falsify</CODE>, and a similar procedure <CODE>verify</CODE> to assert the truth +of a proposition, are implemented in terms of the central procedure +about propositions, <CODE>settruth</CODE>: + +<P><PRE>to verify :a :b +settruth :a :b "true +end + +to falsify :a :b +settruth :a :b "false +end +</PRE> + +<P><CODE>Settruth</CODE> takes three inputs, two individuals and a truth +value. It records the truth or falsehood of the proposition that <CODE>:a</CODE> +is <CODE>:b</CODE>, and uses the rules of inference I've described to derive +other propositions when possible. + +<P><PRE>to settruth :a :b :truth.value +if equalp (gprop :a "category) (gprop :b "category) [stop] +localmake "oldvalue get :a :b +if equalp :oldvalue :truth.value [stop] +if equalp :oldvalue (not :truth.value) ~ + [(throw "error (sentence [inconsistency in settruth] + :a :b :truth.value))] +print (list :a :b "-> :truth.value) +store :a :b :truth.value +settruth1 :a :b :truth.value +settruth1 :b :a :truth.value +if not emptyp :oldvalue ~ + [foreach (filter [equalp first ? :truth.value] :oldvalue) + [apply "settruth butfirst ?]] +end + +to settruth1 :a :b :truth.value +apply (word "find not :truth.value) (list :a :b) +foreach (gprop :a "true) [settruth ? :b :truth.value] +if :truth.value [foreach (gprop :a "false) [falsify ? :b] + pprop :a (gprop :b "category) :b] +pprop :a :truth.value (fput :b gprop :a :truth.value) +end +</PRE> + +<P>If the two individuals are in the same category, <CODE>settruth</CODE> +does nothing. This is to allow for cases such as the example + +<P><PRE>falsify "Jane "Larry +</PRE> + +<P>as explained earlier. If the individuals are in different +categories, the next step is to find what information was previously +available about this proposition. If it was already known to be true +or false, and the truth value input in this call agrees with what was +known, then the program has merely generated some redundant information +and <CODE>settruth</CODE> stops. If the known value disagrees with the input +value, then something is wrong; the program has proven two contradictory +propositions. Generally this means that some clue has been represented +incorrectly in the program. + +<P>If the proposition was not already known to be true or false, then we +have some new information. After notifying the user by printing a +message, <CODE>settruth</CODE> +must store that fact. (Procedures <CODE>get</CODE> and <CODE>store</CODE> are an +interface to the property list primitives that implement the symmetric +rule.) The next step is to make any possible inferences using the +elimination, uniqueness, and transitive rules; this is done separately +for "<CODE>:a</CODE> is <CODE>:b</CODE>" and for "<CODE>:b</CODE> is <CODE>:a</CODE>" by two +calls to the subprocedure <CODE>settruth1</CODE>. + +<P><CODE>Settruth1</CODE> invokes either <CODE>findtrue</CODE> or <CODE>findfalse</CODE> +depending on the truth value. Because of the <CODE>not</CODE> in the +first instruction of <CODE>settruth1</CODE>, <CODE>findtrue</CODE> is called when we are +falsifying a proposition, and vice versa. This makes sense because of +the tasks of these procedures. If we are falsifying a proposition, +then the elimination rule comes into play, and we try to find a true +proposition. If we are verifying a proposition, then the uniqueness +rule lets us find several false propositions on the same row or +column of the chart. The next instructions in <CODE>settruth1</CODE> implement +the transitive rule, looking at other individuals known to be the same +as, or different from, <CODE>:a</CODE>. The last two instructions maintain +the redundant information used for printing the results and for carrying +out the transitive rule. + +<P>The final instruction in <CODE>settruth</CODE> deals with implications. If we +already knew that <EM>p</EM>→<EM>q</EM> and now we're learning that <EM>p</EM> is true, +we can infer that <EM>q</EM> is true. (This is another rule of inference, +which I'll call the <EM>implication</EM> rule.) + +<P><H2>Program Structure: Recording Implications</H2> + +<P>Speaking of implications, we can now explore how the <CODE>says</CODE> procedure +produces and records implications. The instruction + +<P><PRE>says "Jane "Irving 45 +</PRE> + +<P>establishes a relationship between the two propositions +"Jane is Irving" and "Jane is 45." The relationship is that +exactly one of them must be true; the name for this is <EM>exclusive or.</EM> + +<P><PRE>to says :who :what1 :what2 +print (list "says :who :what1 :what2) +xor :who :what1 :who :what2 +end + +to xor :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "false +implies :who1 :what1 "false :who2 :what2 "true +end +</PRE> + +<P><CODE>Says</CODE> is a special case of <CODE>xor</CODE> (a common abbreviation +for exclusive or) in which the two propositions are about a common +individual, Jane in the example. The <CODE>xor</CODE> procedure establishes +two implications, <EM>p</EM> → ¬  <EM>q</EM> and +¬  <EM>p</EM> → <EM>q</EM>. In other words, +if we learn that Jane is Irving, then we can infer that Jane is not 45; +if we learn that Jane is not Irving, we can infer that Jane is 45. +(These two implications are <EM>not</EM> equivalent to each other; in +general, one +might be true and the other false. But the exclusive or relationship +means that both are true.) + +<P>The <CODE>implies</CODE> procedure takes six inputs. The first three are for +one proposition and the others for the second proposition. For each +proposition, two inputs are individuals (call them <EM>x</EM> and <EM>y</EM>) and +the third is <CODE>true</CODE> or <CODE>false</CODE>. If <CODE>true</CODE>, then the +proposition is "<EM>x</EM> is <EM>y</EM>"; if <CODE>false</CODE>, the proposition is +"<EM>x</EM> is not <EM>y</EM>." + +<P>Yet another rule of inference comes into play here, the <EM> +contrapositive</EM> rule. It says +that if <EM>p</EM>→<EM>q</EM> is true, then so is ¬<EM>q</EM> → ¬<EM>p</EM>. +Although these two implications are mathematically equivalent, +we must enter both of them into our data structure because we might +happen to discover that ¬<EM>q</EM> is true, and we'll look for relevant +implications filed under <EM>q</EM> rather than under <EM>p</EM>. + +<P><PRE>to implies :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who2 :what2 (not :truth2) :who1 :what1 (not :truth1) +end +</PRE> + +<P>The first call to <CODE>implies1</CODE> stores the implication +in the form given to us; the second call stores its contrapositive. + +<P><PRE>to implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +localmake "old1 get :who1 :what1 +if equalp :old1 :truth1 [settruth :who2 :what2 :truth2 stop] +if equalp :old1 (not :truth1) [stop] +if memberp (list :truth1 :who2 :what2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +if memberp (list :truth1 :what2 :who2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +store :who1 :what1 ~ + fput (list :truth1 :who2 :what2 :truth2) :old1 +end +</PRE> + +<P>The first three instructions in <CODE>implies1</CODE> check for the +case in which we are told that <EM>p</EM>→<EM>q</EM> but we already know +either <EM>p</EM> or ¬<EM>p</EM>. If we already know <EM>p</EM>, then we can +derive that <EM>q</EM> is true. There's no need to store the implication, +because it is already serving its purpose, which is to allow us to +infer <EM>q</EM>. If we already know ¬<EM>p</EM>, then we can forget about +this implication, because it isn't going to do us any good. We can't +infer anything about <EM>q</EM> from this situation. + +<P>The next two instructions check for the situation in which we +are told <EM>p</EM>→<EM>q</EM> but we already know that <EM>p</EM>→¬<EM>q</EM>. +In that case, <EM>p</EM> must not be true, because if it were, we could +infer two contradictory conclusions. Therefore, we can falsify +the proposition <EM>p</EM>. + +<P>Finally, if none of these conditions is met, we add this implication +to the (possibly empty) list of already known implications about <EM>p</EM>. + +<P><H2>Using Implications to Represent Orderings</H2> + +<P>For another example of implications at work, here's the Logo program +for the Foote problem: + +<P><PRE>to foote.family +cleanup +category "when [1st 2nd 3rd 4th 5th] +category "name [Felix Fred Frank Francine Flo] +category "street [Field Flag Fig Fork Frond] +category "item [food film flashlight fan fiddle] +category "position [1 2 3 4 5] +print [Clue 1] +justbefore "Flag "2nd :position +justbefore "2nd "Fred :position +print [Clue 2] +male [film Fig 5th] +print [Clue 3] +justbefore "flashlight "Fork :position +justbefore "Fork "1st :position +female [1st] +print [Clue 4] +falsify "5th "Frond +falsify "5th "fan +print [Clue 5] +justbefore "Francine "Frank :position +justbefore "Francine "Frank :when +print [Clue 6] +female [3rd Flag] +print [Clue 7] +justbefore "fiddle "Frond :when +justbefore "Flo "fiddle :when +print [] +solution +end +</PRE> + +<P> +I've included <CODE>print</CODE> instructions to let the user know when the +program reaches each of the seven numbered clues. Clue 4 tells us +directly that two possible pairings of individuals are false, and +the program reflects this with two invocations of <CODE>falsify</CODE>. But +the other clues either tell us about the sex of the family members +or tell us that certain individuals are next to each other in an +ordering. The procedures <CODE>male</CODE>, <CODE>female</CODE>, and <CODE>justbefore</CODE> +reflect the language of the problem in the same way that <CODE>says</CODE> +reflected the language of the other problem. + +<P><PRE>to male :stuff +differ sentence :stuff [Francine Flo] +end + +to female :stuff +differ sentence :stuff [Felix Fred Frank] +end +</PRE> + +<P>Needless to say, this implementation of <CODE>male</CODE> and <CODE>female</CODE> +works only for this specific logic problem! It's tempting to try to +use the more general category mechanism this way: + +<P><PRE>category "sex [male female] +verify "Francine "female +verify "Flo "female +verify "Felix "male +verify "Fred "male +verify "Frank "male +</PRE> + +<P>but unfortunately the structure of this inference system +requires that each individual can only match one individual in +another category; once we've verified that Francine is female, +the uniqueness rule will deduce that Flo isn't female! + +<P>On the other hand, I've tried to write <CODE>justbefore</CODE> in a way +that will work for future problems. + +<P><PRE>to justbefore :this :that :lineup +falsify :this :that +falsify :this last :lineup +falsify :that first :lineup +justbefore1 :this :that :lineup +end + +to justbefore1 :this :that :slotlist +if emptyp butfirst :slotlist [stop] +equiv :this (first :slotlist) :that (first butfirst :slotlist) +justbefore1 :this :that (butfirst :slotlist) +end + +to equiv :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "true +implies :who2 :what2 "true :who1 :what1 "true +end +</PRE> + +<P>The input named <CODE>lineup</CODE> is a list of individuals from +an ordering, in the correct order. In this problem, it will be the list + +<P><PRE>[1 2 3 4 5] +</PRE> + +<P>if the clue is about street position, or + +<P><PRE>[1st 2nd 3rd 4th 5th] +</PRE> + +<P>if the clue is about the order of events in time. As I explained +when talking about orderings earlier, the instruction + +<P><PRE>justbefore "Flag "2nd :position +</PRE> + +<P>results in falsifying some propositions: + +<P><PRE>falsify "Flag "2nd +falsify "Flag 5 +falsify "2nd 1 +</PRE> + +<P>and also asserts some implications: + +<P><PRE>implies "Flag 1 "true "2nd 2 "true +implies "2nd 2 "true "Flag 1 "true +implies "Flag 2 "true "2nd 3 "true +implies "2nd 3 "true "Flag 2 "true +implies "Flag 3 "true "2nd 4 "true +implies "2nd 4 "true "Flag 3 "true +implies "Flag 4 "true "2nd 5 "true +implies "2nd 5 "true "Flag 4 "true +</PRE> + +<P><H2>Backtracking</H2> + +<P>This inference system can solve many logic problems, but sometimes it +runs into trouble. I've already mentioned, while discussing the <CODE>male</CODE> +and <CODE>female</CODE> procedures, that the program insists that each individual +in a category must appear exactly once in the solution. Suppose you have +a problem about five people living in five houses; they have five distinct +first names, five last names, five occupations--but two of the houses +are yellow. It's sometimes possible to get around this, but the technique +is a little awkward. You can set up a category like this: + +<P><PRE>category "color [yellow1 yellow2 blue brown green] +</PRE> + +<P>then you find <EM>one</EM> clue that mentions a yellow house +and use <CODE>yellow1</CODE> for that one: + +<P><PRE>verify "Fred "yellow1 +</PRE> + +<P>but for any other mention of something being yellow in the +problem, you represent that by saying that the individual is <EM>not</EM> one +of the other colors: + +<P><PRE>differ "architect [blue brown green] +</PRE> + +<P>You never explicitly mention <CODE>yellow2</CODE> except in setting +up the category. + +<P>That technique works if you know that yellow is the color that appears +twice. What if the problem tells you only that there are five houses +and four colors? Or what if some individuals are <EM>not</EM> in the +solution? For example, a problem might discuss the activities of five +people, each doing something on a different day of the week, but you +don't know until you solve the problem which of the seven weekdays +are involved. + +<P>An entirely different approach to solving logic problems by computer +is <EM>backtracking.</EM> Instead of starting from the clues +and making deductions, a program can start by making arbitrary guesses +about who goes with what, and then use the clues to look for contradictions. +If a contradiction is found, the program systematically makes a different +guess until every possible arrangement has been tried. (Presumably before +every possibility has been tried, one of them will <EM>not</EM> lead to a +contradiction, and that's the solution.) + +<P>In practice, backtracking is a more flexible technique than the inference +system I wrote, because it's easy to let a backtracking program try +multiple appearances of an individual if the problem allows that. But I +thought the inference system would be more interesting to study, for two +reasons. First, the inference system more closely models the way people +solve logic problems. In the cub reporter problem, with four people +to keep straight, there are (4!)<SUP><SMALL>3</SMALL></SUP> or 13,824 possible solutions. In +the Foote problem, with five people, there are (5!)<SUP><SMALL>4</SMALL></SUP> or just over +200 million possibilities. A computer can try them all, but a person +couldn't.<SUP>*</SUP> +(If multiple appearances were allowed, the numbers would be +even higher.) Second, backtracking doesn't work at all unless the problem +deals with a finite set of individuals, as in a logic problem. Inference +systems can be generalized to deal with potentially unbounded problems. + +<P><SMALL><BLOCKQUOTE><SMALL><SUP>*</SUP>People do sometimes use a combination of inference and +backtracking. If, by inference, you've established that Jane must be +either the pilot or the drafter, but you can't settle which, you might +decide to <EM>assume</EM> that Jane is the pilot and hope that you can then +infer either a complete solution to the problem or a contradiction. In the +latter case, you'd know that Jane must be the drafter.</SMALL></BLOCKQUOTE></SMALL><P><H2>Generalized Inference Systems and Predicate Logic</H2> + +<P>The rules of inference in this program are specially designed for problems +like the ones we've just solved. The implication +rule is applicable to any propositional logic situation, but the ones +based on categories, such as the uniqueness and elimination rules, are not. +The idea of a "category" as we've used it +isn't a general principle of logic; instead, that idea should really be +expressed as a series of propositions. For example, to say "there is a +category called `last name' whose members are Irving, King, Mendle, and +Nathan" is really to make several statements of the form "Jane has exactly +one last name," or, in terms of the basic "<EM>x</EM> is <EM>y</EM>" propositions, +<P><CENTER><TABLE><TR><TD>(Jane is Irving) ∨ (Jane is King) +<TR><TD> ∨ (Jane is Mendle) ∨ (Jane is Nathan) +</TABLE></CENTER><P> +and so on. If we wanted to solve this problem in a general +inference system we'd assert the truth of all those propositions at the +beginning. Then if the program discovers that Jane is Irving, it would +have the two propositions +<P><CENTER>¬<STRONG>(</STRONG>(Jane is Irving) +∧ (Jane is King)<STRONG>)</STRONG></CENTER><P> +and +<P><CENTER>(Jane is Irving)</CENTER><P> +and from these it could infer +<P><CENTER>¬(Jane is King)</CENTER><P> +using the standard inference rules of propositional logic. + +<P>The "and so on" just above includes quite a large number of propositions. +And yet this small problem concerns a mere 16 individual names divided into +four categories. For a larger problem it would be nearly impossible to list +all the relevant propositions, and for a problem involving an infinite set +of individuals, such as the integers, it would be literally impossible. What +would make the representation of a problem easier is if we could use, in a +formal system, the same kind of language I used in describing (in English) +the inference rules earlier: "for all other <EM>z</EM> in the same category as +<EM>y</EM>..." There are two parts to such a formal notation. First, in addition +to the <EM>propositional</EM> variables like <EM>p</EM> used in propositional logic, +we need variables like <EM>x</EM> and <EM>y</EM> that can represent objects in the system +we want to describe. Second, we need a notation for "for all." The formal +system including these additions to propositional logic is called <EM> +predicate</EM> logic. The name is like that used in Logo to refer to +operations with <CODE>true</CODE> or <CODE>false</CODE> outputs because +the statements in predicate logic +involve truth-valued functions of objects analogous to the +Logo predicates. For example, the formula we've been representing +informally as "<EM>x</EM> is <EM>y</EM>" is represented formally using the +predicate function is(<EM>x</EM>,<EM>y</EM>). This +is much like the Logo expression + +<P><PRE>equalp :x :y +</PRE> + +<P>A predicate function of two arguments ("inputs" in Logo) is also +called a <EM>relation</EM> in mathematics. Algebraic relations include ones +like = (equal) and < (less than). + +<P>We are almost ready to show how the uniqueness rule can be expressed as a +formula in predicate logic. If you're not accustomed to mathematical +formalism, this formula is a little scary--perhaps the +scariest thing in this book. But I want you to see it so that +you'll appreciate the fact that just <EM>one</EM> formula of predicate logic +can sum up a rule that would require <EM>many</EM> formulas in propositional +logic. I'm going to introduce a new relation called +"isa" that's true if its first argument is a member of its second +argument. The first must be an individual and the second a category. For +example, isa(pilot,job) is true. And the symbol +∀ means "for all." The uniqueness rule says that if <EM>x</EM> is <EM>y</EM> +then <EM>x</EM> can't also be <EM>z</EM> for any <EM>z</EM> in the same category as <EM>y</EM>. Here's +how to say that formally: + + +<P><CENTER>is(<EM>x</EM>,<EM>y</EM>) → ∀<EM>z</EM> +<STRONG>(</STRONG>(isa(<EM>y</EM>,<EM>a</EM>) ∧ isa(<EM>z</EM>,<EM>a</EM>) +∧ ¬(<EM>y</EM>=<EM>z</EM>)<STRONG>)</STRONG></CENTER><P> + +<P>To indicate the linking of two propositions in the general inference system, +no special rules of inference are required. To say "the reporter wrote +down these two statements; one is true and the other false" is just to say +<EM>p</EM>⊗<EM>q</EM>; I'm using the symbol ⊗ to +represent the <EM>exclusive or</EM> function. This formula is equivalent to +<P><CENTER>(<EM>p</EM>∨<EM>q</EM>) ∧ ¬(<EM>p</EM>∧<EM>q</EM>)</CENTER><P> +A general inference system will know that if it's been told <EM>p</EM>⊗<EM>q</EM> +and then later it learns, say, <EM>p</EM> then it can infer ¬<EM>q</EM>. + +<P>The cub reporter problem is simpler than some of its type in that +the only relevant relation among individuals is "is," which is an + +<EM>equivalence</EM> relation. This means that if Jane is Irving then also +Irving is Jane (the technical name for a relation with that property is +<EM>symmetric</EM>), and also that if Jane is Irving, and Irving is the pilot, +then Jane is the pilot (so the relation is <EM>transitive</EM>). It's +relatively easy to work out all the implications of a proposition about +equivalence relations. + +<P> +By contrast, the Foote problem contains <EM>ordering</EM> relations like "is +later than" that are transitive but not symmetric. To handle such problems +the inference system must have a way to represent "<EM>x</EM> is the last." +Other problems contain relations like "lives in the house next to" that +are symmetric but not transitive. A statement like "Mr. Smith lives in the +house at the end" has to be represented formally as something like "there +is only one person <EM>x</EM> such that <EM>x</EM> lives in the house next to Mr. Smith." + +<P>One reason a general inference system is harder to program than the +special-purpose one I've written in this chapter is that my system makes all +possible inferences from any newly verified or falsified proposition. This +is possible only because there is a finite, fairly small number of such +inferences. Once you introduce variables and predicates, the number of +possible inferences is potentially infinite. A general inference system must +take care not to infer infinitely many useless results. One solution is to +defer the making of inferences until the user of the system asks a question, +and then infer only what's needed to answer that particular question. But +it isn't always easy to know exactly what's needed. + +<P>An inference system like the one I'm vaguely describing is a central part of +the programming language Prolog. In that language, you program not by +issuing instructions that tell the computer what to do, but rather by making +<EM>assertions</EM> that some proposition is true. You can then ask questions +like "for what values of <EM>x</EM> is this formula true?" + +<P> +<H2>Logic and Computer Hardware</H2> + + +<P>Besides inference systems, another area in which logic is important in +computer science is in the design of the computers themselves. In a +computer, information is represented as electrical signals flowing through +wires. (These days, a "wire" is likely to be a microscopic conducting +region on a silicon chip rather than a visible strand of metal, but the +principle is the same.) In almost all computers, each wire may be carrying +one of two voltage levels at any moment. (It is the restriction to two +possible voltages that makes them <EM>binary</EM> computers. It would be + +possible to build <EM>ternary</EM> computer circuits using three +voltages, but I know of no practical application of that idea.) A computer +is built out of small circuit elements called <EM>gates</EM> that combine or +rearrange binary signals in various ways. Perhaps the simplest example of a +gate is an <EM>inverter</EM>; it has one input signal and provides one output +signal that is the opposite of the input. That is, if you have a high +voltage coming into the inverter you get a low voltage out, and vice versa. + +<P>The voltages inside the computer can be thought of as representing numbers +(zeros and ones) or truth values (false and true). From now on I'll use the +symbols 0 and 1 to represent the voltages, but you can mentally replace 0 +with <CODE>false</CODE> and 1 with <CODE>true</CODE> to see how what I'm saying here ties +in with what's gone before. + +<P>Suppose you have a gate with two input wires and one output. What are the +possibilities for how that output is determined by the inputs? Each of the +two inputs can have two possible values; that means that a gate has four +different possible input configurations. For each of those four, the gate +can output 0 or 1. As you can see from the chart below, this means that +there are 16 possible kinds of two-input gates: + +<P><CENTER><TABLE> +<TR><TH align="left">input <EM>p</EM>:<TH> 0 +<TH> 0<TH> 1<TH> 1 +<TR><TH align="left">input <EM>q</EM>:<TH> 0 +<TH> 1<TH> 0<TH> 1 +<TR><TD> +<TR><TH align="left">outputs:<TD> 0 +<TD> 0<TD> 0<TD> 0 +<TR><TH><TD> 0<TD> 0<TD> 0<TD> 1<TD> and (<EM>p</EM>∧<EM>q</EM>) +<TR><TH><TD> 0<TD> 0<TD> 1<TD> 0 +<TR><TH><TD> 0<TD> 0<TD> 1<TD> 1 +<TR><TH><TD> 0<TD> 1<TD> 0<TD> 0 +<TR><TH><TD> 0<TD> 1<TD> 0<TD> 1 +<TR><TH><TD> 0<TD> 1<TD> 1<TD> 0<TD> exclusive or (<EM>p</EM>⊗<EM>q</EM>) +<TR><TH><TD> 0<TD> 1<TD> 1<TD> 1<TD> or (<EM>p</EM>∨<EM>q</EM>) +<TR><TH><TD> 1<TD> 0<TD> 0<TD> 0<TD> nor (not-or, ¬(<EM>p</EM>∨<EM>q</EM>)) +<TR><TH><TD> 1<TD> 0<TD> 0<TD> 1<TD> equivalence (<EM>p</EM>↔<EM>q</EM>) +<TR><TH><TD> 1<TD> 0<TD> 1<TD> 0 +<TR><TH><TD> 1<TD> 0<TD> 1<TD> 1 +<TR><TH><TD> 1<TD> 1<TD> 0<TD> 0 +<TR><TH><TD> 1<TD> 1<TD> 0<TD> 1<TD> implies (<EM>p</EM>→<EM>q</EM>) +<TR><TH><TD> 1<TD> 1<TD> 1<TD> 0<TD> nand (not-and, ¬(<EM>p</EM>∧<EM>q</EM>)) +<TR><TH><TD> 1<TD> 1<TD> 1<TD> 1 +</TABLE></CENTER> + +<P>The table indicates, for example, that a gate whose output is 1 +only when both inputs are 1 is an <EM>and</EM> gate, implementing the usual +logical and operation. The 16 possibilities include all the standard logic +functions as well as several less obviously useful ones. Two gate types +called <EM>nand</EM> and <EM>nor</EM> represent functions rarely used in +mathematical logic but common in computer design because it is sometimes +helpful to have the opposite of the signal you're logically interested in. + +<P>Numbers other than 0 and 1 can't be represented as a single signal in a +single wire. That's why there isn't a "plus gate" along with the and +gates, or gates, and so on; if both inputs to a plus gate were 1, the output +would have to be 2. To add two zero-or-one numbers we need a more +complicated device with <EM>two</EM> output wires, one of which is the +"carry" to the next binary digit: + +<P><CENTER><TABLE> +<TR><TH align="left"><EM>A</EM> input:<TH> 0 +<TH> 0<TH> 1<TH> 1 +<TR><TH align="left"><EM>B</EM> input:<TH> 0 +<TH> 1<TH> 0<TH> 1 +<TR><TD> +<TR><TH align="left">sum out:<TD> 0 +<TD> 1<TD> 1<TD> 0 +<TR><TH align="left">carry out:<TD> 0 +<TD> 0<TD> 0<TD> 1 +</TABLE></CENTER> + +<P>These sum and carry outputs can be defined in terms of logical +operations: + +<P> +<P><CENTER><TABLE><TR><TD align="right">Sum<TD> = +<TD> <EM>A</EM>⊗<EM>B</EM> +<TR><TD align="right">Carry<TD> = +<TD> <EM>A</EM>∧<EM>B</EM> +</TABLE></CENTER><P> + + +<P>Exclusive or gates are, in fact, not generally used as basic +hardware components, so this device is traditionally represented in terms of +and gates, or gates, and inverters: + +<P><CENTER><IMG SRC="half-adder.gif" ALT="figure: half-adder"></CENTER> + +<P>The device we've just built is called a <EM>half-adder</EM> for +reasons that should become clear in a moment. + +<P>To represent numbers larger than 1 we have to use more than one signal wire. +Each signal represents a binary digit, or <EM>bit,</EM> that is implicitly +multiplied by a power of 2 just as in the ordinary decimal representation of +numbers each digit is implicitly multiplied by a power of 10. For example, +if we have three signal wires for a number, they have multipliers of 1, 2, +and 4; with these signals we can represent the eight numbers from 0 (all +signals 0) to 7 (all signals 1). When we want to add two such three-bit +numbers, the sum for all but the rightmost bit can involve a carry <EM> +in</EM> as well as a carry out. The circuit for each bit position must have +<EM>three</EM> inputs, including one for the carry from the next bit over as +well as the two external inputs. The outputs are found using these formulas: + +<P> +<P><CENTER><TABLE><TR><TD align="right">Sum<TD> = +<TD> (<EM>A</EM>⊗<EM>B</EM>)⊗CarryIn +<TR><TD align="right">CarryOut<TD> = +<TD> (<EM>A</EM>∧<EM>B</EM>)∨ +<STRONG>(</STRONG>(<EM>A</EM>⊗<EM>B</EM>)∧CarryIn<STRONG>)</STRONG> +</TABLE></CENTER><P> + +<P>This circuit can be built using two half-adders: + +<P><CENTER><IMG SRC="full-adder.gif" ALT="figure: full-adder"></CENTER> + +<P>To add two three-bit numbers we connect three adders together this +way: + +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/three-adders.gif" ALT="figure: three-adders"></CENTER> + +<P>The carry out signal from the leftmost adder (the one representing + +the largest power of 2) is the <EM>overflow</EM> signal; if it's true, the +sum didn't fit in the number of bits provided. Many computers use this +signal to <EM>interrupt</EM> the execution of their programs so that people +don't end up seeing incorrect results. + +<P>The phrase "computer logic" is widely used, even by non-experts, to refer +to the inner workings of a computer. Many people, though, think that the +phrase describes the <EM>personality</EM> of the computer, which they imagine + +to be like that of Mr. Spock. "Computers may be able to play chess, but +they can't write poetry, because that isn't logical." Here you've seen the +real meaning of the phrase: Just as a Logo program has procedures defined in +terms of subprocedures and ultimately in terms of primitive procedures, the +capabilities of a computer itself are built out of smaller pieces, and the +primitive hardware components compute logical, rather than arithmetic, +functions. (For a computer to exhibit Mr. Spock's sense of purpose, +understanding of cause and effect, drive for self-preservation, loyalty to +his species and his government, and so on, would be no less miraculous than +for it to write a love poem or throw a temper tantrum. Later we'll discuss +the efforts of artificial intelligence researchers to produce such miracles.) + +<P><H2>Combinatorics</H2> + + +<P>Earlier I listed the 16 possible logical functions of two logical arguments. +I could have figured out that there are 16 without actually listing them +this way: If a function has two arguments, and each argument has two +possible values, that makes 2<SUP><SMALL>2</SMALL></SUP> possible combinations of argument values. +A logical function is determined by its result for each of those four +possible argument combinations. (The four are <EM>f</EM>(0,0), <EM>f</EM>(0,1), <EM>f</EM>(1,0), +and <EM>f</EM>(1,1).) There are two possible results for <EM>f</EM>(0,0), two for +<EM>f</EM>(0,1), and so on; the number of possible functions is the product of all +these twos, 2<SUP><SMALL>2<SUP><SMALL>2</SMALL></SUP></SMALL></SUP> or 16. + +<P>The mathematics of counting how things can be combined is called +<EM>combinatorics.</EM> The problem we've just done illustrates a fundamental +rule of combinatorics, namely that the number of possibilities for a choice +with several components is the product of the number of possibilities for +each component choice. This may be easier to understand with an example in +which not all the relevant numbers are 2. Here's a classic: Suppose you +have a group of four men and three women, and you want to form a committee +of one man and one woman chosen from this group. How many such committees +are possible? There are 4 choices for the male member of the committee and +3 choices for the female member; that means 4×3 or 12 committees. + +<P>(The multiplication rule only works if the component choices are <EM> +independent</EM>; that is, the possible outcomes of one choice can't be +affected by the outcome of any of the others. For example, if our +committees are to have a chairperson who can be of either sex and then two +other members, one man and one woman, you can't say "there are 7 choices +for the chairperson, times 4 for the man, times 3 for the woman" because +after choosing the chairperson the number of choices for the other members +is changed depending on the sex of the chair. There are two correct ways +to solve this problem. One is to say "The chairperson is either male or +female. If male, there are 4 possible chairs, times 3 possible other male +members, times 3 possible female members, for 36 possible committees. If +female, there are 3 possible chairs, times 4 possible male members, times 2 +possible other female members, for 24 committees. The total is 36+24 or +60 committees." The second solution is to pick the chairperson <EM>last</EM>; +then you say "There are 4 possible male members, times 3 possible females, +times 5 possible chairs (7 people in the original group minus 2 already +chosen)." Apart from arithmetic errors, almost all the mistakes people make +in solving combinatorics problems come from forgetting that events have to +be independent to allow you to multiply the choices.) + +<P>Let's return to logical functions for a moment. Suppose we experiment with +a ternary logic in which the possible values are yes, no, and maybe. (You +can represent these using the numbers 0, 1, and 2.) How many three-argument +ternary logic functions are there? Is it 3<SUP><SMALL>(3<SUP><SMALL>3</SMALL></SUP>)</SMALL></SUP> or is it (3<SUP><SMALL>3</SMALL></SUP>)<SUP><SMALL>3</SMALL></SUP>? +(It doesn't matter which way you group the twos for the binary logic version +because the two groupings have the same value, 16, but this isn't true with +threes.) How many two-argument ternary logic functions are there? +2<SUP><SMALL>(3<SUP><SMALL>2</SMALL></SUP>)</SMALL></SUP>? 3<SUP><SMALL>(2<SUP><SMALL>3</SMALL></SUP>)</SMALL></SUP>? (3<SUP><SMALL>3</SMALL></SUP>)<SUP><SMALL>2</SMALL></SUP>? How many three-argument binary logic +functions? The virtue of these problems is that you can check your own +answers by listing all the possible functions as I did for the two-argument +binary logic functions. + +<P>Most people are introduced to combinatorics +by way of <EM>probability,</EM> +the mathematics of gambling. Given a number of equally likely possible +situations, some of which win a bet and the rest of which lose it, the +probability of winning is a ratio: + +<P><CENTER><IMG SRC="probability.gif"></CENTER><P> +The role of combinatorics is to help in computing the numerator and +denominator of that fraction. + +<P> + +For example, suppose you have six brown socks and four blue socks in a +drawer, and you pull out two socks without looking. What is the probability +of getting a matching pair? I'm going to give each sock a name like +<EM>brown</EM><SUB><SMALL>3</SMALL></SUB> for the third brown sock so that we can talk about individual socks +even if they're the same color. How many possible pairs of socks are there? +That is, given the set +<P><CENTER>{<EM>brown</EM><SUB><SMALL>1</SMALL></SUB>, +<EM>brown</EM><SUB><SMALL>2</SMALL></SUB>, ..., +<EM>brown</EM><SUB><SMALL>6</SMALL></SUB>, +<EM>blue</EM><SUB><SMALL>1</SMALL></SUB>, ... +<EM>blue</EM><SUB><SMALL>4</SMALL></SUB>}</CENTER><P> +containing ten socks, how many two-sock subsets are there? + +<P>The first step in answering this question is to notice that we have 10 +choices for the first sock and then 9 choices for the second. So there are +10×9 ways to make the two choices. (There is a subtle point here +that some textbooks don't bother explaining. The choice of the second sock +is <EM>not</EM> independent of the first choice, since we can't choose the +same sock twice. However, the <EM>number</EM> of second choices is always 9, +even though the particular nine available socks depend on the first choice. +So we can get away with multiplying in this example.) + +<P>This isn't quite the answer we want, though. We've shown that there are 90 +<EM>ordered pairs</EM> of socks. But once we get the socks out of the +drawer, it doesn't matter which we picked first. In other words, if we say +there are 90 possible choices, we are counting +{<EM>brown</EM><SUB><SMALL>2</SMALL></SUB>, <EM>brown</EM><SUB><SMALL>5</SMALL></SUB>} and {<EM>brown</EM><SUB><SMALL>5</SMALL></SUB>, <EM>brown</EM><SUB><SMALL>2</SMALL></SUB>} +as two different choices. Since we don't care which sock came out of the +drawer first, we are really counting every pair twice, so there are only +90/2 or 45 possible pairs. + +<P>An ordered subset of a set is called a <EM>permutation;</EM> +a subset without +a particular order is a <EM>combination.</EM> We say that there are 90 +permutations of ten things taken two at a time; there are 45 combinations of +ten things taken two at a time. + +<P>It turns out that combinations are what matters most of the time; it's +relatively rare for permutations to turn up in a math problem. An exception +is the device wrongly called a "combination lock"; to open one, you must +know a particular permutation of the possible numbers. My high school +locker "combination" was 18-24-14. If I tried the same numbers in a +different order, like 24-18-14, the lock wouldn't open. (Actually it's +misleading for me to use this example because the same number can appear +twice in most locks of this type, so the "combination" is not a subset of +the available numbers. If there are 50 numbers available, the total number +of possibilities is not 50×49×48 but rather 50×50×50. These lock-opening patterns are therefore neither permutations nor +combinations but something else that we might call "permutations with +repetition allowed.") + +<P>We haven't finished solving the sock problem. How many of the possible +pairs of socks are matching pairs? One way to find out would be to list all +the possible pairs and actually count how many of them match. This is the +sort of thing computers do well. First we have to write a procedure that +takes as input a list and a number, and outputs a list of lists, each of +which is a subset of the input list whose length is the input number. That +is, we want to take + +<P><PRE>combs [brown1 brown2 ... brown6 blue1 ... blue4] 2 +</PRE> + +<P>and this should output a list of pairs: + +<P><PRE>[[brown1 brown2] [brown1 brown3] ... [brown4 blue3] ... [blue3 blue4]] +</PRE> + +<P>This is a fairly tricky program to write. Try it before you read +further. Can you reduce the problem to a smaller, similar problem? Don't +forget that we want combinations, not permutations, so the output can't have +two sublists containing the same elements. + +<P>To make sure that each combination appears in the result in only one order, +we can decide explicitly what that order will be. The most convenient thing +is to say that the elements will appear in each sublist in the same order in +which they appear in the original list. That is, since the input list has +<CODE>brown2</CODE> before <CODE>blue3</CODE>, the output will contain the list + +<P><PRE>[brown2 blue3] +</PRE> + +<P>but not the list + +<P><PRE>[blue3 brown2] +</PRE> + +<P>It follows that the very first element of the input list, <CODE> +brown1</CODE>, can only appear as the first element of any output sublist. In +other words, there are two kinds of sublists: ones with <CODE>brown1</CODE> as +their first element and ones that don't include <CODE>brown1</CODE> at all. This +is a way to divide the problem into smaller pieces. + +<P>If we are looking for <EM>n</EM>-element subsets, the first kind consists of <CODE> +brown1</CODE> stuck in front of a smaller subset of <EM>n</EM>−1 elements chosen from the +remainder (the <CODE>butfirst</CODE>) of the input list. The second kind of subset +is an <EM>n</EM>-element subset of the <CODE>butfirst</CODE>. We can collect all of each +kind by a recursive invocation of the procedure we're going to write, then +append the two collections and output the result. So the procedure will +look like this: + +<P><PRE>to combs :list :howmany +... <stop rule> ... +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end +</PRE> + +<P>By now you've had a lot of experience writing +recursive procedures, +but I'm going over this one in detail for two reasons: It's tricky and it's a +model for solving many other combinatorial problems. What makes it tricky +is a combination of two things. One is that it's recursive twice; that is, +there are two recursive invocations of <CODE>combs</CODE> within <CODE>combs</CODE>. This +makes the control structure very different from the + +<P><PRE>to blah :list +output fput (<CODE><EM>something</EM></CODE> first :list) (blah butfirst :list) +end +</PRE> + +<P>sort of recursion that may be more familiar. The second tricky +part is that there are two input variables, each of which may be made smaller +(by <CODE>butfirst</CODE>ing or by subtracting 1) but need not be in a particular +recursive call. + +<P>One implication of these complicating factors is that we need <EM>two</EM> +stop rules. It may be obvious that we need one for the situation of +counting <CODE>:howmany</CODE> down to zero, but we also need one for <CODE>:list</CODE> +getting too small. Ordinarily this latter would be an <CODE>emptyp</CODE> test, but +in fact any list whose length is less than <CODE>:howmany</CODE> is too small, not +just the empty list. Here is the finished procedure: + +<P><PRE>to combs :list :howmany +if equalp :howmany 0 [output [[]]] +if equalp :howmany count :list [output (list :list)] +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end + +? <U>show combs [a b c d e] 3</U> +[[a b c] [a b d] [a b e] [a c d] [a c e] [a d e] + [b c d] [b c e] [b d e] [c d e]] +</PRE> + +<P>Now we can use <CODE>combs</CODE> on the sock problem. (Note: The procedure <CODE> +socks</CODE> shown here is not the one in the program file; there will be a +modified version a few paragraphs down the road.) + +<P><PRE>to socks :list +localmake "total combs :list 2 +localmake "matching filter [equalp butlast first ? butlast last ?] ~ + :total +print (sentence [There are] count :total [possible pairs of socks.]) +print (sentence [Of these,] count :matching [are matching pairs.]) +print sentence [Probability of match =] ~ + word (100*(count :matching)/(count :total)) "% +end + +? <U>socks [brown1 brown2 brown3 brown4 brown5 brown6</U> + <U>blue1 blue2 blue3 blue4]</U> +There are 45 possible pairs of socks. +Of these, 21 are matching pairs. +Probability of match = 46.6666667% +</PRE> + +<P>The answer is that the probability of a matching pair is just +under half. The template used in the invocation of <CODE>filter</CODE> in <CODE> +socks</CODE> depends on the fact that two socks match if their names are equal +except for the last character, such as <CODE>brown3</CODE> and <CODE>brown4</CODE>. + +<P>I've numbered the socks because it's easier for us to talk about how the +program works (and about how the underlying mathematics works, too) if we +can identify an individual sock. But it's worth noting that the program +doesn't really need individual sock names. We could instead use the list + +<P><PRE>[brown brown brown brown brown brown blue blue blue blue] +</PRE> + +<P>and change the <CODE>filter</CODE> template to + +<P><PRE>[equalp first ? last ?] +</PRE> + +<P>The program will generate some <CODE>[brown brown]</CODE> pairs, some +<CODE>[brown blue]</CODE> pairs, and some <CODE>[blue blue]</CODE> pairs. The number of +pairs will still be 45 and the number of matching pairs will still be 21. + +<P>Having come to that realization, we can make the "user interface" a little +smoother by having <CODE>socks</CODE> accept an input list like + +<P><PRE>[6 brown 4 blue] +</PRE> + +<P>and expand that into the desired list of ten socks itself. Here is +the final program: + +<P><PRE>to socks :list +localmake "total combs (expand :list) 2 +localmake "matching filter [equalp first ? last ?] :total +print (sentence [There are] count :total [possible pairs of socks.]) +print (sentence [Of these,] count :matching [are matching pairs.]) +print sentence [Probability of match =] ~ + word (100*(count :matching)/(count :total)) "% +end + +to expand :list +if emptyp :list [output []] +if numberp first :list ~ + [output cascade (first :list) + [fput first butfirst :list ?] + (expand butfirst butfirst :list)] +output fput first :list expand butfirst :list +end + +? <U>socks [6 brown 4 blue]</U> +There are 45 possible pairs of socks. +Of these, 21 are matching pairs. +Probability of match = 46.6666667% +</PRE> + +<P>My reason for presenting this refinement of the program is that it offers a +concrete opportunity for reflection on how you can tell which differences are +important in a combinatorics problem. In discussing the first version of +the program, I said that the two lists + +<P><PRE>[brown2 brown5] and [brown5 brown2] +</PRE> + +<P>represent the same pair of socks, so both shouldn't be included in +the list of lists output by <CODE>combs</CODE>. Now I'm saying that several lists +that look identical like + +<P><PRE>[brown brown] +</PRE> + +<P>represent <EM>different</EM> pairs of socks and must all be counted. +It would be a mistake to say, "There are three possibilities: brown-brown, +brown-blue, and blue-blue. So the probability of a match is 2/3." It's +true that there are three <EM>kinds</EM> of pairs of socks, but the three +kinds are not equally represented in the list of 45 possible pairs. + +<P><H2>Inductive and Closed-Form Definition</H2> + +<P>The usual approach to problems like the one about the socks is not to +enumerate the actual combinations, but rather to compute the <EM>number</EM> +of combinations directly. There are formulas for both number of +combinations and number of permutations. Usually the latter is derived +first because it's easier to understand. + +<P>With 10 socks in the drawer, the number of two-sock permutations is +10×9. If we'd wanted three socks for a visiting extraterrestrial +friend, the number of permutations would be 10×9×8. In +general, if we have <EM>n</EM> things and we want to select <EM>r</EM> of them, the number +of permutations is +<P><CENTER><IMG SRC="math11.gif" ALT="math display"></CENTER><P> +Mathematicians don't like messy formulas full of dots, so this is usually +abbreviated using the factorial function. The notation "<EM>n</EM>!" is +pronounced "<EM>n</EM> factorial" and represents the product of all the integers +from 1 to <EM>n</EM>. Using this notation we can write +<P><CENTER><IMG SRC="math12.gif" ALT="math display"></CENTER><P> +This is an elegant formula, but you should resist the temptation to use it +as the basis for a computer program. If you write + +<P><PRE>to perms :n :r +output (fact :n)/(fact (:n-:r)) +end + +to fact :n +output cascade :n [# * ?] 1 +end +</PRE> + +<P>then you're doing more multiplications than necessary, plus an +unnecessary division. Instead, go back to the earlier version in which <EM>r</EM> +terms are multiplied: + +<P><PRE>to perms :n :r +if :r=0 [output 1] +output :n * perms :n-1 :r-1 +end +</PRE> + +<P>The set of all permutations of <EM>n</EM> things taken <EM>r</EM> at a time includes +several rearrangements of each <EM>combination</EM> of <EM>n</EM> things <EM>r</EM> at a +time. How many rearrangements of each? Each combination is a set of <EM>r</EM> +things, so the number of possible orderings of those <EM>r</EM> things is the +number of permutations of <EM>r</EM> things <EM>r</EM> at a time, <EM><SUB><SMALL>r</SMALL></SUB>P<SUB><SMALL>r</SMALL></SUB></EM> or <EM>r</EM>!. +<EM><SUB><SMALL>n</SMALL></SUB>P<SUB><SMALL>r</SMALL></SUB></EM> is greater than <EM><SUB><SMALL>n</SMALL></SUB>C<SUB><SMALL>r</SMALL></SUB></EM>, the number of combinations of <EM>n</EM> +things taken <EM>r</EM> at a time, by this factor. In other words, if each +combination corresponds to <EM>r</EM>! permutations, then the number of +permutations is <EM>r</EM>! times the number of combinations. So we have +<P><CENTER><IMG SRC="math13.gif" ALT="math display"></CENTER><P> +The notation <IMG SRC="nchooser.gif"> is much more commonly used in mathematics and +computer science texts than <EM><SUB><SMALL>n</SMALL></SUB>C<SUB><SMALL>r</SMALL></SUB></EM>. It's pronounced "<EM>n</EM> choose <EM>r</EM>." + +<P>The traditional way to do the sock problem is this: The total number of +possible pairs of socks is <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/10choose2.gif">. The number of matching pairs is +equal to the number of brown pairs plus the number of blue pairs. The +number of brown pairs is the number of combinations of 6 brown socks chosen +2 at a time, or <IMG SRC="6choose2.gif">. Similarly, the number of pairs of blue socks +is <IMG SRC="4choose2.gif">. So +<P><CENTER><IMG SRC="math14.gif" ALT="math display"></CENTER><P> +which is the same answer we got by enumerating and testing all the possible +pairs. + +<P>A formula like +<P><CENTER><IMG SRC="math15.gif" ALT="math display"></CENTER><P> +defines a mathematical function in terms of other, more elementary functions. +It is comparable to a Logo procedure defined in terms of primitives, like + +<P><PRE>to second :thing +output first butfirst :thing +end +</PRE> + +<P>The "primitives" of mathematics are addition, subtraction, and +so on, along with a few more advanced ones like the trigonometric and +exponential functions. These are called "elementary functions" and a +formula that defines some new function in terms of those is called a +<EM>closed form definition.</EM> + +<P> + +<P>The function <IMG SRC="nchooser.gif"> could also be defined in a different way based on +the ideas in the <CODE>combs</CODE> program we used to enumerate combinations. The +combinations fall into two categories, those that include the first element +and those that don't. So the number of combinations is the sum of the +numbers in each category: +<P><CENTER><IMG SRC="math16.gif" ALT="math display"></CENTER><P> +This is called an <EM>inductive definition.</EM> It is analogous to a +recursive procedure in Logo. + +<P> + +<P>These two formulas provide alternative definitions for the <EM>same</EM> +function, just as two Logo procedures can employ different algorithms but +have the same input-output behavior. How do we know that the two +definitions of <IMG SRC="nchooser.gif"> really do define the same function? Each +definition was derived from the fundamental definition of "the number of +combinations of <EM>n</EM> things taken <EM>r</EM> at a time" by different arguments. +If those arguments are correct, the two versions must define the same +function because there is just one correct number of combinations. It is +also possible to prove the two definitions equivalent by algebraic +manipulation; start with the closed form definition and see if it does, in +fact, obey the requirements of the inductive definition. For example, if +<EM>r</EM>=0 we have +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/math17.gif" ALT="math display"></CENTER><P> +(It may not be obvious that 0! should be equal to 1, but mathematicians +define the factorial function that way so that the formula <EM>n</EM>! = <EM>n</EM>·(<EM>n</EM>−1)! +remains true when <EM>n</EM>=1.) See if you can verify the other two parts of the +inductive definition. Here's a hint: +<P><CENTER><IMG SRC="math18.gif" ALT="math display"></CENTER><P> + +<P>Why would anyone be interested in an inductive definition when the closed +form definition is mathematically simpler and also generally faster to +compute? There are two reasons. First, some functions don't have closed +form definitions in terms of elementary functions. For those functions, +there is no choice but to use an inductive definition. Second, sometimes +when you start with a non-formal definition of a function in terms of its +purpose, like "the number of combinations..." for <IMG SRC="nchooser.gif">, it may be +easier to see how to translate that into an inductive definition as a first +step, even if it later turns out that there is also a less obvious closed +form. In fact, that's what I did in presenting the idea of combinations. I +found it more straightforward to understand the inductive definition because +it made sense to think about the actual combinations and not merely how many +of them there are. (In fact there is a mathematical technique called <EM> +generating functions</EM> that can sometimes be used to transform an +inductive definition into a closed form definition, but that technique +requires calculus and is beyond the scope of this book.) + +<P><H2>Pascal's Triangle</H2> + +<P>In addition to closed form and inductive definitions, it's often helpful to +present a sort of partial definition of a function in the form of a +table of values. (For +logic functions, with only a finite number of possible values +for the arguments of the function, such a table is actually a complete +definition.) Partial definitions in a table of values can be particularly +useful when the function displays some regularity that allows values outside +the table to be computed easily based on the values in the table. For +example, the sine function is <EM>periodic</EM>; its values repeat in cycles +of 360 degrees. If you need to know the sine of 380 degrees, you can look +up the sine of 20 degrees and that's the answer. For functions of two +variables, like addition and multiplication, these function tables are often +presented as square arrays of numbers. In elementary school you learned the +addition and multiplication tables for numbers up to 10, along with +algorithms for reducing the addition and multiplication of larger numbers to +a sequence of operations on single digits. + +<P>The function <IMG SRC="nchooser.gif"> is a function of two variables, so it would +ordinarily be presented as a square table like the multiplication table, +except for the fact that this particular function is meaningfully defined +only when <EM>r</EM>≤<EM>n</EM>. (There are no combinations of three things taken five +at a time, for example, so <IMG SRC="3choose5.gif"> is 0.) So instead of a square +format like this: +<P><CENTER><TABLE> +<TR><TH><SUB><SMALL><EM>r</EM></SMALL></SUB>\<SUP><SMALL><EM>n</EM></SMALL></SUP> +<TH> 0<TH> 1<TH> 2<TH> 3<TH> 4<TH> 5 +<TR><TH>0<TD align="center"> 1<TD align="center"> 1<TD align="center"> 1 +<TD align="center"> 1<TD align="center"> 1<TD align="center"> 1 +<TR><TH>1<TD align="center"> 0<TD align="center"> 1<TD align="center"> 2 +<TD align="center"> 3<TD align="center"> 4<TD align="center"> 5 +<TR><TH>2<TD align="center"> 0<TD align="center"> 0<TD align="center"> 1 +<TD align="center"> 3<TD align="center"> 6<TD align="center"> 10 +<TR><TH>3<TD align="center"> 0<TD align="center"> 0<TD align="center"> 0 +<TD align="center"> 1<TD align="center"> 4<TD align="center"> 10 +<TR><TH>4<TD align="center"> 0<TD align="center"> 0<TD align="center"> 0 +<TD align="center"> 0<TD align="center"> 1<TD align="center"> 5 +<TR><TH>5<TD align="center"> 0<TD align="center"> 0<TD align="center"> 0 +<TD align="center"> 0<TD align="center"> 0<TD align="center"> 1 +</TABLE></CENTER><P> +this function is traditionally presented in a triangular form called +"Pascal's Triangle" after Blaise Pascal (1623-1662), who invented the +mathematical theory of probability along with Pierre de Fermat (1601-1665). +Pascal didn't invent the triangle, but he did pioneer its use in +combinatorics. Each row of the triangle contains the nonzero values of +<IMG SRC="nchooser.gif"> for a particular <EM>n</EM>: +<P><CENTER><TABLE> +<TR><TD align="center">1 +<TR><TD align="center">1 1 +<TR><TD align="center">1 2 1 +<TR><TD align="center">1 3 3 1 +<TR><TD align="center">1 4 6 4 1 +<TR><TD align="center">1 5 10 10 5 1 +</TABLE></CENTER><P> +Pascal's Triangle is often introduced in algebra because the numbers in row +<EM>n</EM> (counting from zero) are the <EM>binomial coefficients,</EM> the constant +factors in the terms in the expansion of (<EM>a</EM>+<EM>b</EM>)<SUP><SMALL><EM>n</EM></SMALL></SUP>. For example, +<P><CENTER><IMG SRC="math21.gif" ALT="math display"></CENTER><P> + +<P>Do you see why the binomial coefficients are related to combinations? An +expression like (<EM>a</EM>+<EM>b</EM>)<SUP><SMALL>4</SMALL></SUP> is a sum of products of four <EM>A</EM>s and <EM>B</EM>s. (How +many such products? Each term involves four choices between <EM>A</EM> and <EM>B</EM>; +there are 2 ways to make each choice, and the choices are independent, so +there are 2<SUP><SMALL>4</SMALL></SUP> possible products.) These products are combined into terms +based on the fact that some are equal to each other, such as <EM>aaab</EM> and +<EM>abaa</EM>, both of which contribute to the <EM>a</EM><SUP><SMALL>3</SMALL></SUP><EM>b</EM> term. How many arrangements +of three <EM>A</EM>s and one <EM>B</EM> are there? That's like asking how many ways there +are to choose one slot for a <EM>B</EM> out of four possible slots, which is +<IMG SRC="4choose1.gif">. + +<P>Can you predict what the coefficients will be in the expansion of +(<EM>a</EM>+<EM>b</EM>+<EM>c</EM>)<SUP><SMALL>4</SMALL></SUP>? For example, what is the coefficient of <EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM>? Try +to multiply it out and see if your formula is right. + +<P>Everyone is taught in school that each number in Pascal's Triangle, except +for the 1s at the ends, is the sum of the two numbers above it. But this is +usually presented as a piece of magic with no explanation. It's not obvious +how that fact is connected to the formula expressing <IMG SRC="nchooser.gif"> in terms +of factorials. But the technique I used in writing the <CODE>combs</CODE> procedure +to enumerate the actual combinations explains how Pascal's Triangle works. +The set of all combinations of <EM>n</EM> things taken <EM>r</EM> at a time can be divided +into those combinations that include the first of the <EM>n</EM> things and those +that don't. How many of the former are there? Each such combination must +be completed by adjoining to that first thing <EM>r</EM>−1 out of the remaining +<EM>n</EM>−1 available things, so there are <IMG SRC="n-1chooser-1.gif"> such combinations. +The second category, those not containing the first thing in the list, +requires us to choose <EM>r</EM> things out of the remaining <EM>n</EM>−1, so there are +<IMG SRC="n-1chooser.gif"> of them. So <IMG SRC="nchooser.gif"> must be the sum of those two +numbers, which are indeed the ones above it in the triangle. + +<P>Thinking about the triangle may also help you to understand why <CODE>combs</CODE> +needs two stop rules; each row contains <EM>two</EM> numbers, the ones (pun) +at each end, that can't be computed as the sum of two other numbers. + +<P><H2>Simulation</H2> + + +<P>Yet another approach to solving the sock problem would be the +experimental method: Load a drawer with six brown and four blue socks, pull out pairs +of socks a few thousand times, and see how many of the pairs match. The +actual experiment would be time-consuming and rather boring, but we can +<EM>simulate</EM> the experiment with a computer program. The idea is to use +random numbers to represent the random choice of a sock. + +<P><PRE>to socktest +localmake "first ~ + pick [brown brown brown brown brown brown blue blue blue blue] +localmake "second ~ + pick (if equalp :first "brown + [[brown brown brown brown brown blue blue blue blue]] + [[brown brown brown brown brown brown blue blue blue]] ) +output equalp :first :second +end +</PRE> + +<P><CODE>Socktest</CODE> is a predicate that simulates one trial of picking +a pair of socks and outputs <CODE>true</CODE> if the socks match. Notice how the +available choices for the second sock depend on which color sock was chosen +first. (It's a little unaesthetic that this particular selection of six +brown and four blue socks is built into the program, with three slightly +different lists explicitly present inside <CODE>socktest</CODE>. It would be both +more elegant and more flexible if <CODE>socktest</CODE> could take a list like +<CODE>[6 brown 4 blue]</CODE> as input, like <CODE>socks</CODE>, and compute the list of +possibilities for the second sock itself. But right now I'm more interested +in showing how a simulation works than in programming style; you can make +that change yourself if you like.) + +<P>What we want to do is invoke <CODE>socktest</CODE> repeatedly and keep track of how +many times the output is <CODE>true</CODE>. That can be done with an instruction +like + +<P><PRE>print (cascade 1000 [? + if socktest [1] [0]] 0) / 10 +</PRE> + +<P>I divide by 10 so that the result will be expressed as a percent +probability. (If I made 100 trials instead of 1000 the output from <CODE> +cascade</CODE> would already be a percentage.) Your results will depend on the +random number generator of your computer. I tried it three times and got +results of 50.1%, 50.8%, and 45.5%. I then did 10,000 trials at once +with a result of 48.78%. The result expected on theoretical grounds was +46 <SUP><SMALL>2</SMALL></SUP>⁄<SUB><SMALL>3</SMALL></SUB>%. + +<P>Simulation is generally much slower than either of the techniques we used +earlier (enumeration of possibilities and direct computation of the number +of possibilities), and it gives results that are only approximately correct. +So why would anyone want to use this method? For a simple problem like +this, you probably wouldn't. But some combinatorics problems are too +complicated to be captured by a simple formula. For example, what is the +probability of winning a game of solitaire? (To make this a sensible +question, you'd have to decide on a particular set of strategy rules to +determine which card to play next when there are several possibilities. The +rule could be "play the higher ranking card" or "choose a card at +random," for example.) In principle this question could be answered +exactly, since there are only a finite number of ways a deck of cards can be +arranged and we could analyze each of them. But in practice the most +reasonable approach is probably to write a solitaire simulator and have it +play out a few thousand randomly ordered hands. + +<P>Solitaire is a rather complicated game; even a simulator for it would be +quite a large project. A more manageable one, if you'd like something to +program, would be a craps simulator. Remember that the 11 possible results +of rolling two dice (2 to 12) are not equally likely! You have to simulate +each die separately. + +<P><H2>The Simplex Lock Problem</H2> + +<P>This is a picture of a Simplex lock, so called because it's +manufactured by Simplex Security Systems, Inc. It is a five-button mechanical +(i.e., no electricity) combination lock with an unusual set of possible +combinations. As an example of a challenging problem in combinatorics, I'd +like you to figure out how many possible combinations there are. + +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/lock.gif" ALT="figure: lock"></CENTER> + + + +<P>What makes this lock unusual is that a combination can include more than one +button pushed at the same time. For example, one possible combination is +"2, then 1 and 4 at the same time, then 3." Here are the precise rules: + +<P><P> +<TABLE><TR><TH align="right" valign="top">1.<TD> <TD valign="top"> Each button may be used at most once. For example, "2, then 2 and 3 at +the same time" is not allowed. +<TR><TH align="right" valign="top">2.<TD> <TD valign="top"> Each push may include any number of buttons, from one to five. For +example, one legal combination is "hit all five buttons at once with your +fist." (But hitting all five buttons can't be part of a larger combination +because of rule 1.) + +<P></TABLE><P> + +<P>It follows from these rules that there can be at most five +distinct pushes. (Do you see why?) The rules also allow for the null +combination, in which you don't have to push any buttons at all. + +<P>When working on this problem, don't forget that when two or more buttons are +pushed at the same time, their order doesn't matter. That is, you shouldn't +count "2 and 3 together, then 5" and "3 and 2 together, then 5" as two +distinct combinations. (For this reason, the Simplex lock <EM>is</EM> +entitled, at least in part, to the name "combination lock"!) + +<P>Try to figure out how many combinations there are before reading further. +You can enumerate all the possibilities or you can derive a formula for the +number of possibilities. You might want to start with a smaller number of +buttons. (As a slight hint, when you buy one of these locks, the box it +comes in says "thousands of combinations.") + +<P>I first attacked this problem by trying to enumerate all the possible +combinations, but that turns out to be quite messy. The trouble is that it +isn't obvious how to <EM>order</EM> the combinations, so it's hard to be sure +you haven't missed any. Here is how I finally decided to do it. First of +all, divide the possible combinations into six categories depending on how +many buttons (zero to five) they use. There is exactly one combination +using zero buttons, and there are five using one button each. After that it +gets tricky because there are different <EM>patterns</EM> of simultaneous +pushes within each category. For example, for combinations using two +buttons there are two patterns: the one in which they're pressed together +(<CODE>x-x</CODE>) and the one in which they're pressed separately (<CODE>x x</CODE>). +(I'm introducing a notation for patterns in which hyphens connect buttons +that are pressed together and spaces connect the separate pushes.) How many +distinct combinations are there in each of those patterns? Figure it out +before reading on. + +<P>In the <CODE>x x</CODE> pattern there are <SUB><SMALL>5</SMALL></SUB><EM>P</EM><SUB><SMALL>2</SMALL></SUB> "combinations" because the +order in which you push the buttons matters. In the <CODE>x-x</CODE> pattern there +are only <IMG SRC="5choose2.gif"> combinations because the two buttons are pushed +together; <CODE>1-4</CODE> and <CODE>4-1</CODE> are the same combination. Altogether +there are 20+10 or 30 combinations usng two of the five buttons. + +<P>Beyond this point it gets harder to keep track of the different patterns. +Among the three-button patterns are <CODE>x-x x</CODE>, <CODE>x x x</CODE>, and <CODE> +x-x-x</CODE>. How many more are there? How many four-button patterns? You might, +at this point, like to see if you can finish enumerating all the +possibilities for the five-button lock. + +<P>My solution is to notice that in a three-button pattern, for example, there +are two slots between the <CODE>x</CODE>s, and each slot has a space or a hyphen. +If I think of those slots as binary digits, with 0 for space and 1 for +hyphen, then each pattern corresponds to a 2-bit number. There are four +such numbers, 00 to 11 (or 0 to 3 in ordinary decimal notation). + +<P><TABLE><TR><TH>number<TH> <TH>pattern +<TR><TD align="center"> +<PRE> +00 +01 +10 +11 +</PRE><TH> <TD align="center"> +<PRE> +x x x +x x-x +x-x x +x-x-x +</PRE></TABLE> + +<P>Similarly, there are eight four-button patterns: + +<P><TABLE><TR><TH>number<TH> <TH>pattern +<TR><TD align="center"> +<PRE> +000 +001 +010 +011 +100 +101 +110 +111 +</PRE><TH> <TD align="center"> +<PRE> +x x x x +x x x-x +x x-x x +x x-x-x +x-x x x +x-x x-x +x-x-x x +x-x-x-x +</PRE></TABLE> + +<P>And there are 16 five-button patterns, from 0000 to 1111. + +<P>How many combinations are there within each pattern? There are two +different ways to go about calculating that number. To be specific, let's +consider four-button patterns. The way I chose to do the calculation was to +start with the idea that there are <SUB><SMALL>5</SMALL></SUB><EM>P</EM><SUB><SMALL>4</SMALL></SUB> ways to choose four buttons in +order. For the <CODE>x x x x</CODE> pattern, this is the answer. For the other +patterns, this number (120) has to be divided by various factors to account +for the fact that the order is <EM>partially</EM> immaterial, just as in +deriving the formula for combinations from the formula for permutations we +divided by <EM>r</EM>! because the order is completely immaterial. Consider the +pattern <CODE>x-x x x</CODE>. In this pattern the order of the first two numbers +is immaterial, but the choice of the first two numbers as a pair matters, +and so does the order of the last two numbers. So <CODE>1-2 3 4</CODE> is the same +combination as <CODE>2-1 3 4</CODE> but different from <CODE>1-3 2 4</CODE> or <CODE> +1-2 4 3</CODE>. That means the number 120 is too big by a factor of 2, because +every significant choice of combination is represented twice. For this +pattern the number of different combinations is 60. Of course the same +argument applies to the patterns <CODE>x x-x x</CODE> and <CODE>x x x-x</CODE>. + +<P>What about <CODE>x-x x-x</CODE>? In this pattern there are two pairs of positions +within which order doesn't matter. Each combination appears <EM>four</EM> +times in the list of 120; <CODE>1-2 3-4</CODE> is the same as <CODE>1-2 4-3</CODE>, +<CODE>2-1 3-4</CODE>, and <CODE>2-1 4-3</CODE>. So there are 30 significantly different +combinations in this pattern. What about <CODE>x-x-x x</CODE>? In this pattern, +the order of the first three numbers is irrelevant; this means that there +are 3! or 6 appearances of each combination in the 120, so there are 20 +significantly different combinations in this pattern. The general rule is +that for each group of <EM>m</EM> consecutive hyphens in the pattern you must +divide by (<EM>m</EM>+1)! to eliminate duplicates. + +<P>(My approach was to start with permutations and then divide out redundant +ones. Another approach would be to build up the pattern using combinations. +The pattern <CODE>x-x x x</CODE> contains three groups of numbers representing +three "pushes": a group of two and two groups of one. Since this is a +five-button lock, for the first group of two there are <IMG SRC="5choose2.gif"> choices. +(Order doesn't matter within a group.) For the second group there are only +three buttons remaining from which we can choose, so there are <IMG SRC="3choose1.gif"> +choices for that button. Finally, there are <IMG SRC="2choose1.gif"> choices for the +fourth button (the third group). This makes 10×3×2 possible +combinations for this pattern, the same as the 60 we computed the other way. +For the <CODE>x-x x-x</CODE> pattern this method gives <IMG SRC="5c2x3c2.gif"> +or 30 combinations.) + +<P>Having worked all this out, I was ready to write a computer program to count +the total number of combinations. The trickiest part was deciding how to +deal with the binary numbers that represent the patterns. In the end I used +plain old numbers. The expression + +<P><PRE>remainder :number 2 +</PRE> + +<P>yields the rightmost bit of a number, and then <CODE>:number/2</CODE> +gives all but the rightmost bit (with a little extra effort for odd numbers). +To help you read the program, here is a description of the most important +procedures: + +<P> +<TABLE><TR><TH align="right" valign="top"><CODE>lock 5</CODE><TD> <TD valign="top">outputs the total number of combinations +for the 5-button lock. +<TR><TH align="right" valign="top"><CODE>lock1 5 4</CODE><TD> <TD valign="top">outputs the number of combinations that use +4 out of the 5 buttons. +<TR><TH align="right" valign="top"><CODE>lock2 120 5 1</CODE><TD> <TD valign="top">outputs the number of combinations for the +4-button pattern corresponding to the binary +form of the number 5 (101 or x-x x-x). The +120 is <SUB><SMALL>5</SMALL></SUB><EM>P</EM><SUB><SMALL>4</SMALL></SUB> and the 1 is always used as +the third input except in recursive calls. + +<P></TABLE> + +<P>Here is the program: + +<P><PRE>to lock :buttons +output cascade :buttons [? + lock1 :buttons #] 1 +end + +to lock1 :total :buttons +localmake "perms perms :total :buttons +output cascade (twoto (:buttons-1)) ~ + [? + lock2 :perms #-1 1] ~ + 0 +end + +to twoto :power +output cascade :power [2 * ?] 1 +end + +to lock2 :perms :links :factor +if equalp :links 0 [output :perms/(fact :factor)] +if equalp (remainder :links 2) 0 ~ + [output lock2 :perms/(fact :factor) :links/2 1] +output lock2 :perms (:links-1)/2 :factor+1 +end +</PRE> + +<P>One slight subtlety is that in <CODE>lock</CODE> the third input to +<CODE>cascade</CODE> is 1 rather than 0 to include the one 0-button combination +that would not otherwise be added in. + +<P><H2>An Inductive Solution</H2> + +<P>When I wrote that program, I was pleased with myself for managing to turn +such a messy solution into executable form, but I wasn't satisfied with +the underlying approach. I wanted something mathematically more elegant. + +<P>What made it possible for me to find the approach I wanted was the chance +discovery that the number of combinations that use all five buttons (541) +is half of the total number of combinations (1082). Could this possibly be +a coincidence, or would that have to be true for any number of buttons? +To see that it has to be true, I used an idea from another branch of +mathematics, <EM>set theory.</EM> A <EM>set</EM> is any collection of things, +in no particular order. One can speak of the set of all the fingers on my +left hand, or the set of all the integers, or the set of all the universities +in cities named Cambridge. Much of the interesting part of set theory has +to do with the properties of infinite sets; for example, it turns out that +the set of all the integers is the same size as the set of all the rational +numbers, but both of these are smaller than the set of irrational numbers. +What does it mean for one infinite set to be the same size as, or to be +larger than, another? The same definition works equally well for finite +sets: Two sets are the same size if they can be placed in +<EM>one-to-one correspondence.</EM> This means that you must exhibit a way to +pair the elements of one set with the elements of the other so that each +element of one has exactly one partner in the other. (A set is larger than +another if they aren't the same size, but a subset of the first is the same +size as the second.) + +<P>To prove that my observation about the lock combinations has to be true +regardless of the number of buttons, I have to exhibit a one-to-one +correspondence between two sets: the set of all combinations using all +the buttons of an <EM>n</EM>-button lock and the set of all combinations using +fewer than <EM>n</EM> of the buttons. But that's easy. Starting with a +combination that uses all the buttons, just eliminate the last push (one or +more buttons pushed at the same time) to get a combination using fewer than +all the buttons. For example, for a five-button lock, the five-button +combination <CODE>2 3-4 1-5</CODE> is paired with the three-button combination +<CODE>2 3-4</CODE>. (We have to eliminate the last <EM>push</EM> and not merely +the last <EM>button</EM> for two reasons. First, if we always eliminated +exactly one button, we'd always get a four-button combination, and we want +to pair five-button combinations with all the fewer-than-five ones. +Second, which is the "last" button if the last push involves more than +one? Remember, <CODE>2 3-4 1-5</CODE> is the <EM>same</EM> combination as +<CODE>2 3-4 5-1</CODE>. But writing this combination in two different forms +seems to pair it with two different smaller ones. The rules of one-to-one +correspondence say that each element of a set must have exactly one partner +in the other set.) + +<P>To show that the correspondence works in both directions, start with a +combination that doesn't use all the buttons; its partner is formed by +adding one push at the end that contains all the missing buttons. +For example, if we start with <CODE>1 2-5</CODE> then its partner is +<CODE>1 2-5 3-4</CODE>. + +<P>I've just proved that the number of all-<EM>n</EM> combinations must be equal to +the number of fewer-than-<EM>n</EM> combinations. So it's not a coincidence that +541 is half of 1082. In order to be able to talk about these numbers more +succinctly, I want to define +<P><CENTER><EM>f</EM>(<EM>n</EM>) = number of <EM>n</EM>-button +combinations of an <EM>n</EM>-button lock</CENTER><P> +We've just proved that it's also true that +<P><CENTER><EM>f</EM>(<EM>n</EM>) = number of fewer-than-<EM>n</EM>-button +combinations</CENTER><P> +Now, what does "fewer than <EM>n</EM> buttons" mean? Well, there are +combinations using no buttons, one button, two buttons, and so on up to <EM>n</EM>−1 +buttons. Let's define +<P><CENTER><EM>g</EM>(<EM>n</EM>,<EM>i</EM>) = number of <EM>i</EM>-button +combinations in an <EM>n</EM>-button lock</CENTER><P> +So we can formalize the phrase "fewer than <EM>n</EM>" by saying +<P><CENTER><EM>f</EM>(<EM>n</EM>) = +<EM>g</EM>(<EM>n</EM>,0)+<EM>g</EM>(<EM>n</EM>,1)+<EM>g</EM>(<EM>n</EM>,2)+ ··· +<EM>g</EM>(<EM>n</EM>,<EM>n</EM>−1)</CENTER><P> +Instead of using those dots in the middle, mathematicians have another +notation for a sum of several terms like this. +<P><CENTER><IMG SRC="math26.gif" ALT="math display"></CENTER><P> +If you haven't seen this notation before, the Σ (<EM>sigma</EM>) +symbol is the Greek letter <EM>S,</EM> and is used to represent a <EM>S</EM>um. +It works a little like the <CODE>for</CODE> iteration tool; the variable below the +Σ (in this case, <EM>i</EM>) takes on values from the lower limit (0) to the +upper limit (<EM>n</EM>−1), and for each of those values the expression following the +Σ is added into the sum. The Logo equivalent would be + +<P><PRE>for [i 0 [:n-1]] [make "sum :sum + (g :n :i)] +</PRE> + +<P>The Σ-expression is pronounced "the sum from <EM>i</EM> equals +zero to <EM>n</EM> minus one of <EM>g</EM> of <EM>n</EM> comma <EM>i</EM>." + +<P>So far, what I've done is like what I did before: dividing the set of all +possible combinations into subsets based on the number of buttons used in +each combination. This is like the definition of <CODE>lock</CODE> in terms of +<CODE>lock1</CODE>. The next step is to see if we can find a formula for <EM>g</EM>(<EM>n</EM>,<EM>i</EM>). +How many 3-button combinations, for example, can we make using a 5-button +lock? (That's <EM>g</EM>(5,3).) There are many different ways in which I might +try to derive a formula, but I think it will be helpful at this point to +step back and consider my overall goal. I started this line of reasoning +because I'm trying to express the solution for the five-button lock in terms +of easier solutions for smaller numbers of buttons. That is, I'm looking +for an inductive definition of <EM>f</EM>(<EM>n</EM>) in terms of values of <EM>f</EM> for smaller +arguments. I'd like to end up with a formula like +<P><CENTER><EM>f</EM>(<EM>n</EM>) = ... <EM>f</EM>(0) ... <EM>f</EM>(1) +... <EM>f</EM>(<EM>n</EM>−1) ...</CENTER><P> +but I don't yet know exactly what form it will take. So far I've written +a formula for <EM>f</EM>(<EM>n</EM>) in terms of <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) for values of <EM>i</EM> less than <EM>n</EM>. +It would be great, therefore, if I could express <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) in terms of +<EM>f</EM>(<EM>i</EM>); that would give me exactly what I want. + +<P>To put that last sentence into words, it would be great if I could express +the number of <EM>i</EM>-button combinations of an <EM>n</EM>-button lock in terms of the +number of <EM>i</EM>-button combinations of an <EM>i</EM>-button lock. For example, can I +express the number of combinations using 3 out of 5 buttons in terms of the +number of combinations of 3 out of 3 buttons? Yes, I can. The latter is +the number of rearrangements of three buttons once we've selected the three +buttons. If we start with five buttons, there are <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/5choose3.gif"> possible +sets of three buttons to choose. For each of those <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/5choose3.gif"> sets of +three buttons, there are <EM>f</EM>(3) ways to arrange those three buttons in a +combination. + +<P> + +<P><P><CENTER><IMG SRC="math28.gif" ALT="math display"></CENTER><P> +It may not be obvious why this is so. Suppose you list all the 3-button +combinations of a 3-button lock. There are 13 of them, consisting of the +numbers from 1 to 3 in various orders and with various groups connected +by hyphens. Those 13 combinations are also some of the 3-button combinations +of a 5-button lock, namely, the ones in which the particular three buttons +we chose are 1, 2, and 3. If instead we choose a different set of three +(out of five) buttons, that gives rise to a different set of 13 combinations. +For example, if we choose the buttons 2, 3, and 4, we can take the original +13 combinations and change all the 1s to 2s, all the 2s to 3s, and all the +3s to 4s: + +<P><PRE>buttons: 1,2,3 2,3,4 1,4,5 + + 1 2 3 2 3 4 1 4 5 + 1 3 2 2 4 3 1 5 4 + 2 1 3 3 2 4 4 1 5 + 2 3 1 3 4 2 4 5 1 + 3 1 2 4 2 3 5 1 4 + 3 2 1 4 3 2 5 4 1 + 1 2-3 2 3-4 1 4-5 + 2 1-3 3 2-4 4 1-5 + 3 1-2 4 2-3 5 1-4 + 1-2 3 2-3 4 1-4 5 + 1-3 2 2-4 3 1-5 4 + 2-3 1 3-4 2 4-5 1 + 1-2-3 2-3-4 1-4-5 +</PRE> + +<P>This table has a column for each of three possible combinations of +five numbers three at a time. The table could be extended to have a column +for <EM>every</EM> such combination of numbers, and then it would contain all +the lock combinations using three out of five buttons. The total number of +entries in the extended table is therefore <EM>g</EM>(5,3); the table has <EM>f</EM>(3) +rows and <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/5choose3.gif"> columns. So +<P><CENTER><IMG SRC="math29.gif" ALT="math display"></CENTER><P> +which is a particular case of the general formula above. + +<P>We now have a formula for <EM>f</EM>(<EM>n</EM>) in terms of all the <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) and a formula +for <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) in terms of <EM>f</EM>(<EM>i</EM>). Combining these we have +<P><CENTER><IMG SRC="math30.gif" ALT="math display"></CENTER><P> +or +<P><CENTER><IMG SRC="math31.gif" ALT="math display"></CENTER><P> +Like any inductive definition, this one needs a special rule for the +smallest case, from which all the others are computed: +<P><CENTER><EM>f</EM>(0) = 1</CENTER><P> + +<P>The total number of combinations for an <EM>n</EM>-button lock is 2×<EM>f</EM>(<EM>n</EM>). +I find this much more elegant than my original solution. (So why didn't I +just show you this one to begin with? Because I never would have figured +this one out had I not first done the enumeration of cases. I want you to +see how a combinatorics problem is solved, not just what the beautiful +solution looks like.) This formula can also be turned into a computer +program: + +<P><PRE>to simplex :buttons +output 2 * f :buttons +end + +to f :n +if equalp :n 0 [output 1] +output cascade :n [? + ((choose :n (#-1)) * f (#-1))] 0 +end + +to choose :n :r +output (perms :n :r)/(fact :r) +end +</PRE> + +<P>This program is faster as well as simpler than the other; on my +home computer, <CODE>lock 5</CODE> takes about 4 seconds, <CODE>simplex 5</CODE> about 2 seconds. + +<P>The <CODE>simplex</CODE> function has no exact closed form equivalent, but it turns +out that there is (amazingly!) a closed form definition that, when rounded +to the nearest integer, gives the desired value: + +<P><PRE>to simp :n +output round (fact :n)/(power (ln 2) (:n+1)) +end +</PRE> + +<P>The <CODE>ln</CODE> function, a Logo primitive, computes the "natural +logarithm" of its input; <CODE>ln 2</CODE> has the approximate value 0.69314718056. +The <CODE>power</CODE> function of two inputs takes +the first input to the power of the second input. <CODE>Fact</CODE> is the +factorial function as defined earlier in this chapter. + +<P>Another related programming problem is to list the actual combinations, +rather than merely count them. Probably the simplest way to do that is +to use an approach similar to the one I used in the <CODE>combs</CODE> procedure +that lists combinations of members of a list: First use recursion to +find the lock combinations using only the <CODE>butfirst</CODE> of the available +buttons, then find the ways in which the <CODE>first</CODE> button can be added +to each of them. + +<P><H2>Multinomial Coefficients</H2> + + +<P>Earlier, in talking about Pascal's Triangle, I showed how binomial +coefficients are related to combinations and asked you to think about +<EM>trinomial</EM> coefficients. What, for example, is the coefficient of +<EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM> in the expansion of (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>)<SUP><SMALL>4</SMALL></SUP>? + +<P>The expansion is a sum of products; each of those products contains four +variables (<EM>aaaa</EM>, <EM>aaab</EM>, etc.). The ones that contribute to the <EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM> +term are the ones with one <EM>A</EM>, two <EM>B</EM>s, and one <EM>c</EM>; these include +<EM>abbc</EM>, <EM>bcab</EM>, <EM>cabb</EM>, and so on. Out of the four slots for variables in +one of those products, how many ways can we choose a slot for one <EM>A</EM>? The +answer is <IMG SRC="4choose1.gif">. Having chosen one, we are left with three slots +and we want to choose two of them for <EM>B</EM>s. There are <IMG SRC="3choose2.gif"> ways to +do that. Then we have one slot left, just enough for the one <EM>c</EM>, which +makes a trivial contribution of <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/1choose1.gif"> to the overall number of +possibilities. The total is <IMG SRC="4c1x3c2x1c1.gif"> or 4×3×1 or 12, and that is the coefficient of +<EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM>. Similarly, the coefficient of <EM>ac</EM><SUP><SMALL>3</SMALL></SUP> is <IMG SRC="4c1x3c3.gif"> or 4. + +<P>The same sort of argument can be used for even more complicated cases. In +the expansion of (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>+<EM>d</EM>+<EM>e</EM>)<SUP><SMALL>14</SMALL></SUP> what is the coefficient of <EM>a</EM><SUP><SMALL>2</SMALL></SUP><EM>b</EM><SUP><SMALL>3</SMALL></SUP><EM>c</EM><EM>d</EM><SUP><SMALL>5</SMALL></SUP><EM>e</EM><SUP><SMALL>3</SMALL></SUP>? +It's <P><CENTER><IMG SRC="math33.gif" ALT="math display"></CENTER><P> + +<P>Here is a harder question: How many terms are there in, say, (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>+<EM>d</EM>)<SUP><SMALL>7</SMALL></SUP>? +It's easy to see that there are 4<SUP><SMALL>7</SMALL></SUP> products of four variables, but after +the ones that are equal to each other have been combined into terms, how +many distinct terms are there? + +<P>Like the Simplex lock problem, this one can probably be solved most easily +by reducing the problem to a smaller subproblem--in other words, by an +inductive definition. This problem also has something in common with the +earlier problem of listing all the combinations of a given size from a +given list, as we did in the <CODE>combs</CODE> procedure. Try to solve the +problem before reading further. (It's hard to say how another person will +find a problem, but I think this one is easier than the Simplex one.) + +<P>In order to be able to express the original problem in terms of a smaller +version, we have to generalize it. I posed a specific problem, about the +seventh power of the sum of four variables. I'd like to be able to give +the answer to that problem the name <EM>t</EM>(4,7) and try to find a way to +express that in terms of, let's say, <EM>t</EM>(4,6). So I'm going to define +the function <EM>t</EM> as +<P><CENTER><EM>t</EM>(<EM>n</EM>,<EM>k</EM>) = number of terms +in (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>+<EM>a</EM><SUB><SMALL>2</SMALL></SUB>+ + ··· ++<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL><EM>k</EM></SMALL></SUP></CENTER><P> +(If this were a "straight" math book I'd cheerfully recycle the name <EM>f</EM> +for the function, even though we had a different <EM>f</EM> in the last section, +but I'm anticipating wanting to write a Logo program for this problem and I +can't have two procedures named <CODE>f</CODE> in the same workspace.) + +<P>In writing <CODE>combs</CODE> I used the trick of dividing all possible +combinations into two groups: those including the first member of the list +and those not including that member. A similar trick will be useful here; +we can divide all the terms in an expansion into two groups. One group will +contain those terms that include the first variable (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>) and the other +will contain the rest. For example, in the original problem, <EM>a</EM><SUP><SMALL>2</SMALL></SUP><EM>b</EM><SUP><SMALL>3</SMALL></SUP><EM>d</EM><SUP><SMALL>2</SMALL></SUP> is +a term in the first group, while <EM>c</EM><SUP><SMALL>7</SMALL></SUP> is a term in the second group. + +<P>A term in the first group can be divided by <EM>a</EM><SUB><SMALL>1</SMALL></SUB>; the result must be a term +in the expansion of (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>+<EM>a</EM><SUB><SMALL>2</SMALL></SUB>+ ··· +<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL><EM>k</EM>−1</SMALL></SUP>. How many such terms are +there? There are <EM>t</EM>(<EM>n</EM>,<EM>k</EM>−1) of them. So that's how many terms there are in +the first group. + +<P>A term in the second group is a product of <EM>k</EM> variables <EM>not</EM> +including <EM>a</EM><SUB><SMALL>1</SMALL></SUB>. That means that such a term is also part of the expansion +of (<EM>a</EM><SUB><SMALL>2</SMALL></SUB>+ ··· +<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL><EM>k</EM></SMALL></SUP>. How many such terms are there? There are +<EM>t</EM>(<EM>n</EM>−1,<EM>k</EM>) of them. Notice the difference between the two groups. In the +first case, we associate a term with a similar term in the expansion of an +expression involving a <EM>smaller power</EM> of the <EM>same number</EM> of +variables. In the second case, we associate a term with an equal term in +the expansion of an expression involving <EM>fewer variables</EM> taken to +the <EM>same power.</EM> + +<P>Combining these two results, we see that +<P><CENTER><EM>t</EM>(<EM>n</EM>,<EM>k</EM>) = +<EM>t</EM>(<EM>n</EM>,<EM>k</EM>−1)+<EM>t</EM>(<EM>n</EM>−1,<EM>k</EM>)</CENTER><P> +Since this is a function of two variables, it needs two "stop rules," just +like the function <IMG SRC="nchooser.gif">. Picking these limiting cases seems much +simpler than inventing the induction rule, but even so, it may repay some +attention. For the rule +<P><CENTER><IMG SRC="math36.gif" ALT="math display"></CENTER><P> +we ended up considering the limiting cases <EM>r</EM>=0 and <EM>r</EM>=<EM>n</EM>. I didn't say +anything about it at the time because I didn't want to get distracted, but +it's not obvious why there is the asymmetry between the two variables in +those limiting cases. That is, why didn't I pick <EM>r</EM>=0 and <EM>n</EM>=0 as the +limiting cases? That would be more like what you're accustomed to in +recursive Logo procedures, where stop rules almost always involve a +comparison of something with zero or with the empty list. + +<P>The funny limiting cases for <IMG SRC="nchooser.gif"> (and the corresponding funny stop +rules in <CODE>combs</CODE>) are related to the fact that this function is +meaningful only when <EM>n</EM>≥<EM>r</EM>. The two arguments can't be chosen +independently. If we didn't have the <EM>r</EM>=<EM>n</EM> limiting case, the inductive +formula would have us compute +<P><CENTER><IMG SRC="math37.gif" ALT="math display"></CENTER><P> +If we define <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/4choose5.gif"> as zero, this equation does turn out to be true, +but it isn't a very sensible way to compute <IMG SRC="5choose5.gif">. + +<P>In the case of the function <EM>t</EM>, the two arguments <EM>are</EM> independent. +Both <EM>t</EM>(4,7) and <EM>t</EM>(7,4) are sensible things to ask for. Therefore, we +should use the more obvious limiting cases <EM>n</EM>=0 and <EM>k</EM>=0. The trouble is +that it's not obvious what the value of <EM>t</EM>(0,<EM>k</EM>) or <EM>t</EM>(<EM>n</EM>,0) should be. The +first of these, <EM>t</EM>(0,<EM>k</EM>), represents the number of terms in the expansion of +()<SUP><SMALL><EM>k</EM></SMALL></SUP>--nothing to the <EM>k</EM>th power! That seems meaningless. On the other +hand, <EM>t</EM>(<EM>n</EM>,0) represents the number of terms in (∑ <EM>a</EM><SUB><SMALL><EM>i</EM></SMALL></SUB>)<SUP><SMALL>0</SMALL></SUP>, which is 1. +Anything to the zeroth power is 1. Does "1" count as a term? It doesn't +have any variables in it. + +<P> + +<P>One solution would be to take as limiting cases <EM>n</EM>=1 and <EM>k</EM>=1. It's much +easier to see what those values should be. (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>)<SUP><SMALL><EM>k</EM></SMALL></SUP> has one term, so +<EM>t</EM>(1,<EM>k</EM>)=1. And (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>+ ··· +<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL>1</SMALL></SUP> has <EM>n</EM> terms, so <EM>t</EM>(<EM>n</EM>,1)=<EM>n</EM>. We +could, then, define the function <EM>t</EM> as +<P><CENTER><IMG SRC="math38.gif" ALT="math display"></CENTER><P> +But it is possible to figure out appropriate values for zero arguments by +working backwards from the cases we already understand. For example, we +know that <EM>t</EM>(2,1) must equal 2. But +<P><CENTER><EM>t</EM>(2,1) = <EM>t</EM>(2,0)+<EM>t</EM>(1,1) = <EM>t</EM>(2,0)+1</CENTER><P> +It follows that <EM>t</EM>(2,0) must be 1. So it's reasonable to guess that +<EM>t</EM>(<EM>n</EM>,0)=1 will work in general. Similarly, we know that <EM>t</EM>(1,2)=1, but +<P><CENTER><EM>t</EM>(1,2) = <EM>t</EM>(1,1)+<EM>t</EM>(0,2) = 1+<EM>t</EM>(2,0)</CENTER><P> +Therefore <EM>t</EM>(0,2) must be 0. We can define <EM>t</EM> as +<P><CENTER><IMG SRC="math41.gif" ALT="math display"></CENTER><P> + +<P>What is <EM>t</EM>(0,0)? The definition above contradicts itself about this. The +answer should be 0 because <EM>n</EM>=0 but also 1 because <EM>k</EM>=0. This reminds me +of the similar problem about powers of integers. What is 0<SUP><SMALL>0</SMALL></SUP>? In general +0<SUP><SMALL><EM>x</EM></SMALL></SUP>=0 but <EM>x</EM><SUP><SMALL>0</SMALL></SUP>=1, for nonzero <EM>x</EM>. There is really no "right" answer, +but mathematicians have adopted the convention that 0<SUP><SMALL>0</SMALL></SUP>=1. To make our +definition of <EM>t</EM> truly correct I have to choose a convention for <EM>t</EM>(0,0) +and modify the definition to reflect it: +<P><CENTER><IMG SRC="math42.gif" ALT="math display"></CENTER><P> + +<P> + +<P>It's straightforward to translate this mathematical function definition into +a Logo procedure: + +<P><PRE>to t :n :k +if equalp :k 0 [output 1] +if equalp :n 0 [output 0] +output (t :n :k-1)+(t :n-1 :k) +end +</PRE> + +<P>Using this function we can compute <CODE>t 4 7</CODE> and find that the +answer to the original problem is 120. + +<P>(Can you write a program to display the actual expansion? That is, it +should print something like + +<P><PRE>(A+B+C+D)^7 = + 1 A^7 + + 7 A^6 B + + 21 A^5 B^2 + + ... +</PRE> + +<P>There are two parts to this problem. One is to figure out the +combinations of variables in the 120 terms, which can be done with a +procedure like <CODE>combs</CODE>, and the other is to figure out the coefficients, +which I discussed at the beginning of this section.) + +<P>I was introduced to this problem as a student teacher in a high school +probability class. The teacher gave "how many terms are there in the +expansion of (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>+<EM>d</EM>)<SUP><SMALL>7</SMALL></SUP>" as a quiz problem, and nobody answered it. +In the ensuing class discussion, it turned out that she meant the students +to answer the much easier question of how many products of seven variables +there are. As I noted earlier, the answer to <EM>that</EM> question is just +4<SUP><SMALL>7</SMALL></SUP>. But all the students interpreted the question as meaning the harder +one we've been exploring here. I took the problem home that evening and +reached the point we've reached in this chapter. I didn't think I could get +a better answer than that until my housemate taught me about +generating functions. It turns out that there <EM>is</EM> a +closed form definition for +this function: +<P><CENTER><IMG SRC="math43.gif" ALT="math display"></CENTER><P> +This definition is faster to compute as well as more beautiful. + +<P>Once armed with the formula, it wasn't hard to invent a way to demonstrate +that it must be correct without going through the inductive definition and +the use of calculus. The trick is that we must be choosing <EM>n</EM>−1 somethings +out of a possible <EM>k</EM>+<EM>n</EM>−1 for each term. What does a term look like? +Ignoring the constant coefficient, it is the product of <EM>k</EM> (seven, in the +specific problem given) variables, some of which may be equal. Furthermore, +when the terms are written in the usual way, the variables come in +alphabetical order. A term like <EM>a</EM><SUP><SMALL>2</SMALL></SUP><EM>b</EM><SUP><SMALL>4</SMALL></SUP><EM>d</EM> represents <EM>aabbbbd</EM>; there won't +be a different term with the same letters in another order. In general, the +<EM>k</EM> variables will be some number (zero or more) of <EM>a</EM><SUB><SMALL>1</SMALL></SUB>s, then some number +of <EM>a</EM><SUB><SMALL>2</SMALL></SUB>s, and so on. + +<P>Now comes the trick. Suppose we write the string of variables with a +"wall" for each change to the next letter. So instead of <EM>aabbbbd</EM> I want +to write <EM>aa</EM>|<EM>bbbb</EM>||<EM>d</EM>. (There are two walls before the +final <EM>d</EM> to reflect the fact that we skipped over <EM>c</EM>.) In this notation +there are always exactly <EM>n</EM>−1 walls. (That's why I chose to put the walls +in; remember, we're looking for <EM>n</EM>−1 of something.) The term includes <EM>k</EM> +variables and <EM>n</EM>−1 walls, for a total of <EM>k</EM>+<EM>n</EM>−1 symbols. + +<P>Once the walls are there, it really is no longer necessary to preserve the +individual variable letters. The sample term we've been using could just as +well be written <EM>xx</EM>|<EM>xxxx</EM>||<EM>x</EM>. What comes before the first +wall is the first variable letter, and so on. So ||<EM>xxx</EM>|<EM>xxxx</EM> represents <EM>c</EM><SUP><SMALL>3</SMALL></SUP><EM>d</EM><SUP><SMALL>4</SMALL></SUP>. But now we're finished. We have found a way to +represent each possible term as a string of <EM>k</EM> copies of the letter <EM>x</EM> +interspersed with <EM>n</EM>−1 walls. How many such arrangements are there? How +many ways are there to choose <EM>n</EM>−1 positions for walls in a string of +<EM>k</EM>+<EM>n</EM>−1 symbols? + +<P>Earlier, in talking about the difference between closed form and inductive +definitions, I suggested that the an inductive definition might be much +easier to discover even if a closed form definition also exists. This is a +clear example. If I'd given the demonstration just above, with <EM>x</EM>s and +walls, without first showing you the more roundabout way I really discovered +the definition, you'd rightly complain about rabbits out of hats. + +<P> +<TABLE width="100%"><TR><TD><A HREF="../v3-toc2.html">(back to Table of Contents)</A> +<TD align="right"><A HREF="../v3ch1/v3ch1.html"><STRONG>BACK</STRONG></A> +chapter thread <A HREF="../v3ch3/v3ch3.html"><STRONG>NEXT</STRONG></A> +</TABLE> + +<P><H2>Program Listing</H2> + +<P><P> +<P><PRE> +;;; Logic problem inference system + +;; Establish categories + +to category :category.name :members +print (list "category :category.name :members) +if not namep "categories [make "categories []] +make "categories lput :category.name :categories +make :category.name :members +foreach :members [pprop ? "category :category.name] +end + +;; Verify and falsify matches + +to verify :a :b +settruth :a :b "true +end + +to falsify :a :b +settruth :a :b "false +end + +to settruth :a :b :truth.value +if equalp (gprop :a "category) (gprop :b "category) [stop] +localmake "oldvalue get :a :b +if equalp :oldvalue :truth.value [stop] +if equalp :oldvalue (not :truth.value) ~ + [(throw "error (sentence [inconsistency in settruth] + :a :b :truth.value))] +print (list :a :b "-> :truth.value) +store :a :b :truth.value +settruth1 :a :b :truth.value +settruth1 :b :a :truth.value +if not emptyp :oldvalue ~ + [foreach (filter [equalp first ? :truth.value] :oldvalue) + [apply "settruth butfirst ?]] +end + +to settruth1 :a :b :truth.value +apply (word "find not :truth.value) (list :a :b) +foreach (gprop :a "true) [settruth ? :b :truth.value] +if :truth.value [foreach (gprop :a "false) [falsify ? :b] + pprop :a (gprop :b "category) :b] +pprop :a :truth.value (fput :b gprop :a :truth.value) +end + +to findfalse :a :b +foreach (filter [not equalp get ? :b "true] peers :a) ~ + [falsify ? :b] +end + +to findtrue :a :b +if equalp (count peers :a) (1+falses :a :b) ~ + [verify (find [not equalp get ? :b "false] peers :a) + :b] +end + +to falses :a :b +output count filter [equalp "false get ? :b] peers :a +end + +to peers :a +output thing gprop :a "category +end + +;; Common types of clues + +to differ :list +print (list "differ :list) +foreach :list [differ1 ? ?rest] +end + +to differ1 :a :them +foreach :them [falsify :a ?] +end + +to justbefore :this :that :lineup +falsify :this :that +falsify :this last :lineup +falsify :that first :lineup +justbefore1 :this :that :lineup +end + +to justbefore1 :this :that :slotlist +if emptyp butfirst :slotlist [stop] +equiv :this (first :slotlist) :that (first butfirst :slotlist) +justbefore1 :this :that (butfirst :slotlist) +end + +;; Remember conditional linkages + +to implies :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who2 :what2 (not :truth2) :who1 :what1 (not :truth1) +end + +to implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +localmake "old1 get :who1 :what1 +if equalp :old1 :truth1 [settruth :who2 :what2 :truth2 stop] +if equalp :old1 (not :truth1) [stop] +if memberp (list :truth1 :who2 :what2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +if memberp (list :truth1 :what2 :who2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +store :who1 :what1 ~ + fput (list :truth1 :who2 :what2 :truth2) :old1 +end + +to equiv :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "true +implies :who2 :what2 "true :who1 :what1 "true +end + +to xor :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "false +implies :who1 :what1 "false :who2 :what2 "true +end + +;; Interface to property list mechanism + +to get :a :b +output gprop :a :b +end + +to store :a :b :val +pprop :a :b :val +pprop :b :a :val +end + +;; Print the solution + +to solution +foreach thing first :categories [solve1 ? butfirst :categories] +end + +to solve1 :who :order +type :who +foreach :order [type "| | type gprop :who ?] +print [] +end + +;; Get rid of old problem data + +to cleanup +if not namep "categories [stop] +ern :categories +ern "categories +erpls +end + +;; Anita Harnadek's problem + +to cub.reporter +cleanup +category "first [Jane Larry Opal Perry] +category "last [Irving King Mendle Nathan] +category "age [32 38 45 55] +category "job [drafter pilot sergeant driver] +differ [Jane King Larry Nathan] +says "Jane "Irving 45 +says "King "Perry "driver +says "Larry "sergeant 45 +says "Nathan "drafter 38 +differ [Mendle Jane Opal Nathan] +says "Mendle "pilot "Larry +says "Jane "pilot 45 +says "Opal 55 "driver +says "Nathan 38 "driver +print [] +solution +end + +to says :who :what1 :what2 +print (list "says :who :what1 :what2) +xor :who :what1 :who :what2 +end + +;; Diane Baldwin's problem + +to foote.family +cleanup +category "when [1st 2nd 3rd 4th 5th] +category "name [Felix Fred Frank Francine Flo] +category "street [Field Flag Fig Fork Frond] +category "item [food film flashlight fan fiddle] +category "position [1 2 3 4 5] +print [Clue 1] +justbefore "Flag "2nd :position +justbefore "2nd "Fred :position +print [Clue 2] +male [film Fig 5th] +print [Clue 3] +justbefore "flashlight "Fork :position +justbefore "Fork "1st :position +female [1st] +print [Clue 4] +falsify "5th "Frond +falsify "5th "fan +print [Clue 5] +justbefore "Francine "Frank :position +justbefore "Francine "Frank :when +print [Clue 6] +female [3rd Flag] +print [Clue 7] +justbefore "fiddle "Frond :when +justbefore "Flo "fiddle :when +print [] +solution +end + +to male :stuff +differ sentence :stuff [Francine Flo] +end + +to female :stuff +differ sentence :stuff [Felix Fred Frank] +end + +;;; Combinatorics toolkit + +to combs :list :howmany +if equalp :howmany 0 [output [[]]] +if equalp :howmany count :list [output (list :list)] +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end + +to fact :n +output cascade :n [# * ?] 1 +end + +to perms :n :r +if equalp :r 0 [output 1] +output :n * perms :n-1 :r-1 +end + +to choose :n :r +output (perms :n :r)/(fact :r) +end + +;; The socks problem + +to socks :list +localmake "total combs (expand :list) 2 +localmake "matching filter [equalp first ? last ?] :total +print (sentence [there are] count :total [possible pairs of socks.]) +print (sentence [of these,] count :matching [are matching pairs.]) +print sentence [probability of match =] ~ + word (100 * (count :matching)/(count :total)) "% +end + +to expand :list +if emptyp :list [output []] +if numberp first :list ~ + [output cascade (first :list) + [fput first butfirst :list ?] + (expand butfirst butfirst :list)] +output fput first :list expand butfirst :list +end + +to socktest +localmake "first pick [brown brown brown brown brown brown + blue blue blue blue] +localmake "second ~ + pick (ifelse equalp :first "brown ~ + [[brown brown brown brown brown + blue blue blue blue]] ~ + [[brown brown brown brown brown brown + blue blue blue]]) +output equalp :first :second +end + +;; The Simplex lock problem + +to lock :buttons +output cascade :buttons [? + lock1 :buttons #] 1 +end + +to lock1 :total :buttons +local "perms +make "perms perms :total :buttons +output cascade (twoto (:buttons-1)) [? + lock2 :perms #-1 1] 0 +end + +to lock2 :perms :links :factor +if equalp :links 0 [output :perms/(fact :factor)] +if equalp (remainder :links 2) 0 ~ + [output lock2 :perms/(fact :factor) :links/2 1] +output lock2 :perms (:links-1)/2 :factor+1 +end + +to twoto :power +output cascade :power [2 * ?] 1 +end + +to simplex :buttons +output 2 * f :buttons +end + +to f :n +if equalp :n 0 [output 1] +output cascade :n [? + ((choose :n (#-1)) * f (#-1))] 0 +end + +to simp :n +output round (fact :n)/(power (ln 2) (:n+1)) +end + +;; The multinomial expansion problem + +to t :n :k +if equalp :k 0 [output 1] +if equalp :n 0 [output 0] +output (t :n :k-1)+(t :n-1 :k) +end +</PRE><P> + + + +<P><A HREF="../v3-toc2.html">(back to Table of Contents)</A> +<P><A HREF="../v3ch1/v3ch1.html"><STRONG>BACK</STRONG></A> +chapter thread <A HREF="../v3ch3/v3ch3.html"><STRONG>NEXT</STRONG></A> + +<P> +<ADDRESS> +<A HREF="../index.html">Brian Harvey</A>, +<CODE>bh@cs.berkeley.edu</CODE> +</ADDRESS> +</BODY> +</HTML> diff --git a/js/games/nluqo.github.io/~bh/v3ch2/math.lg b/js/games/nluqo.github.io/~bh/v3ch2/math.lg new file mode 100644 index 0000000..8893ef8 --- /dev/null +++ b/js/games/nluqo.github.io/~bh/v3ch2/math.lg @@ -0,0 +1,315 @@ +;;; Logic problem inference system + +;; Establish categories + +to category :category.name :members +print (list "category :category.name :members) +if not namep "categories [make "categories []] +make "categories lput :category.name :categories +make :category.name :members +foreach :members [pprop ? "category :category.name] +end + +;; Verify and falsify matches + +to verify :a :b +settruth :a :b "true +end + +to falsify :a :b +settruth :a :b "false +end + +to settruth :a :b :truth.value +if equalp (gprop :a "category) (gprop :b "category) [stop] +localmake "oldvalue get :a :b +if equalp :oldvalue :truth.value [stop] +if equalp :oldvalue (not :truth.value) ~ + [(throw "error (sentence [inconsistency in settruth] + :a :b :truth.value))] +print (list :a :b "-> :truth.value) +store :a :b :truth.value +settruth1 :a :b :truth.value +settruth1 :b :a :truth.value +if not emptyp :oldvalue ~ + [foreach (filter [equalp first ? :truth.value] :oldvalue) + [apply "settruth butfirst ?]] +end + +to settruth1 :a :b :truth.value +apply (word "find not :truth.value) (list :a :b) +foreach (gprop :a "true) [settruth ? :b :truth.value] +if :truth.value [foreach (gprop :a "false) [falsify ? :b] + pprop :a (gprop :b "category) :b] +pprop :a :truth.value (fput :b gprop :a :truth.value) +end + +to findfalse :a :b +foreach (filter [not equalp get ? :b "true] peers :a) ~ + [falsify ? :b] +end + +to findtrue :a :b +if equalp (count peers :a) (1+falses :a :b) ~ + [verify (find [not equalp get ? :b "false] peers :a) + :b] +end + +to falses :a :b +output count filter [equalp "false get ? :b] peers :a +end + +to peers :a +output thing gprop :a "category +end + +;; Common types of clues + +to differ :list +print (list "differ :list) +foreach :list [differ1 ? ?rest] +end + +to differ1 :a :them +foreach :them [falsify :a ?] +end + +to justbefore :this :that :lineup +falsify :this :that +falsify :this last :lineup +falsify :that first :lineup +justbefore1 :this :that :lineup +end + +to justbefore1 :this :that :slotlist +if emptyp butfirst :slotlist [stop] +equiv :this (first :slotlist) :that (first butfirst :slotlist) +justbefore1 :this :that (butfirst :slotlist) +end + +;; Remember conditional linkages + +to implies :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who2 :what2 (not :truth2) :who1 :what1 (not :truth1) +end + +to implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +localmake "old1 get :who1 :what1 +if equalp :old1 :truth1 [settruth :who2 :what2 :truth2 stop] +if equalp :old1 (not :truth1) [stop] +if memberp (list :truth1 :who2 :what2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +if memberp (list :truth1 :what2 :who2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +store :who1 :what1 ~ + fput (list :truth1 :who2 :what2 :truth2) :old1 +end + +to equiv :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "true +implies :who2 :what2 "true :who1 :what1 "true +end + +to xor :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "false +implies :who1 :what1 "false :who2 :what2 "true +end + +;; Interface to property list mechanism + +to get :a :b +output gprop :a :b +end + +to store :a :b :val +pprop :a :b :val +pprop :b :a :val +end + +;; Print the solution + +to solution +foreach thing first :categories [solve1 ? butfirst :categories] +end + +to solve1 :who :order +type :who +foreach :order [type "| | type gprop :who ?] +print [] +end + +;; Get rid of old problem data + +to cleanup +if not namep "categories [stop] +ern :categories +ern "categories +erpls +end + +;; Anita Harnadek's problem + +to cub.reporter +cleanup +category "first [Jane Larry Opal Perry] +category "last [Irving King Mendle Nathan] +category "age [32 38 45 55] +category "job [drafter pilot sergeant driver] +differ [Jane King Larry Nathan] +says "Jane "Irving 45 +says "King "Perry "driver +says "Larry "sergeant 45 +says "Nathan "drafter 38 +differ [Mendle Jane Opal Nathan] +says "Mendle "pilot "Larry +says "Jane "pilot 45 +says "Opal 55 "driver +says "Nathan 38 "driver +print [] +solution +end + +to says :who :what1 :what2 +print (list "says :who :what1 :what2) +xor :who :what1 :who :what2 +end + +;; Diane Baldwin's problem + +to foote.family +cleanup +category "when [1st 2nd 3rd 4th 5th] +category "name [Felix Fred Frank Francine Flo] +category "street [Field Flag Fig Fork Frond] +category "item [food film flashlight fan fiddle] +category "position [1 2 3 4 5] +print [Clue 1] +justbefore "Flag "2nd :position +justbefore "2nd "Fred :position +print [Clue 2] +male [film Fig 5th] +print [Clue 3] +justbefore "flashlight "Fork :position +justbefore "Fork "1st :position +female [1st] +print [Clue 4] +falsify "5th "Frond +falsify "5th "fan +print [Clue 5] +justbefore "Francine "Frank :position +justbefore "Francine "Frank :when +print [Clue 6] +female [3rd Flag] +print [Clue 7] +justbefore "fiddle "Frond :when +justbefore "Flo "fiddle :when +print [] +solution +end + +to male :stuff +differ sentence :stuff [Francine Flo] +end + +to female :stuff +differ sentence :stuff [Felix Fred Frank] +end + +;;; Combinatorics toolkit + +to combs :list :howmany +if equalp :howmany 0 [output [[]]] +if equalp :howmany count :list [output (list :list)] +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end + +to fact :n +output cascade :n [# * ?] 1 +end + +to perms :n :r +if equalp :r 0 [output 1] +output :n * perms :n-1 :r-1 +end + +to choose :n :r +output (perms :n :r)/(fact :r) +end + +;; The socks problem + +to socks :list +localmake "total combs (expand :list) 2 +localmake "matching filter [equalp first ? last ?] :total +print (sentence [there are] count :total [possible pairs of socks.]) +print (sentence [of these,] count :matching [are matching pairs.]) +print sentence [probability of match =] ~ + word (100 * (count :matching)/(count :total)) "% +end + +to expand :list +if emptyp :list [output []] +if numberp first :list ~ + [output cascade (first :list) + [fput first butfirst :list ?] + (expand butfirst butfirst :list)] +output fput first :list expand butfirst :list +end + +to socktest +localmake "first pick [brown brown brown brown brown brown + blue blue blue blue] +localmake "second ~ + pick (ifelse equalp :first "brown ~ + [[brown brown brown brown brown + blue blue blue blue]] ~ + [[brown brown brown brown brown brown + blue blue blue]]) +output equalp :first :second +end + +;; The Simplex lock problem + +to lock :buttons +output cascade :buttons [? + lock1 :buttons #] 1 +end + +to lock1 :total :buttons +localmake "perms perms :total :buttons +output cascade (twoto (:buttons-1)) [? + lock2 :perms #-1 1] 0 +end + +to lock2 :perms :links :factor +if equalp :links 0 [output :perms/(fact :factor)] +if equalp (remainder :links 2) 0 ~ + [output lock2 :perms/(fact :factor) :links/2 1] +output lock2 :perms (:links-1)/2 :factor+1 +end + +to twoto :power +output cascade :power [2 * ?] 1 +end + +to simplex :buttons +output 2 * f :buttons +end + +to f :n +if equalp :n 0 [output 1] +output cascade :n [? + ((choose :n (#-1)) * f (#-1))] 0 +end + +to simp :n +output round (fact :n)/(power (ln 2) (:n+1)) +end + +;; The multinomial expansion problem 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b/js/games/nluqo.github.io/~bh/v3ch2/v3ch2.html new file mode 100644 index 0000000..194753f --- /dev/null +++ b/js/games/nluqo.github.io/~bh/v3ch2/v3ch2.html @@ -0,0 +1,2870 @@ +<HTML> +<HEAD> +<TITLE>Computer Science Logo Style vol 3 ch 2: Discrete Mathematics</TITLE> +</HEAD> +<BODY> +<CITE>Computer Science Logo Style</CITE> volume 3: +<CITE>Beyond Programming</CITE> 2/e Copyright (C) 1997 MIT +<H1>Discrete Mathematics</H1> + +<TABLE width="100%"><TR><TD> +<IMG SRC="../csls3.jpg" ALT="cover photo"> +<TD><TABLE> +<TR><TD align="right"><CITE><A HREF="http://www.cs.berkeley.edu/~bh/">Brian +Harvey</A><BR>University of California, Berkeley</CITE> +<TR><TD align="right"><BR> +<TR><TD align="right"><A HREF="../pdf/v3ch02.pdf">Download PDF version</A> +<TR><TD align="right"><A HREF="../v3-toc2.html">Back to Table of Contents</A> +<TR><TD align="right"><A HREF="../v3ch1/v3ch1.html"><STRONG>BACK</STRONG></A> +chapter thread <A HREF="../v3ch3/v3ch3.html"><STRONG>NEXT</STRONG></A> +<TR><TD align="right"><A HREF="https://mitpress.mit.edu/books/computer-science-logo-style-second-edition-volume-3">MIT +Press web page for <CITE>Computer Science Logo Style</CITE></A> +</TABLE></TABLE> + +<HR><P>Program file for this chapter: <A HREF="math.lg"><CODE>math</CODE></A> + + + +<P>Computer scientists often use mathematics as a tool in their work, but the +mathematical problems that arise in computer science are of a special kind. +Consider these examples: + +<P>Suppose you have a nondeterministic FSM with five states and you want to +convert it to a deterministic one. What is the largest number of states +that might be required for the new machine? Well, each state of the new +machine corresponds to some <EM>combination</EM> of states of the old one, +because the conversion works by finding multiple transitions (from some state +via the same input character to multiple states) and creating a new state +that combines all those resulting states. How many such combinations are +possible? In other words, how many <EM>subsets</EM> does a five-element set +have? The answer is 2<SUP><SMALL>5</SMALL></SUP> or 32 states. (31, really, because one of those +is the empty subset and that will never be used.) + +<P>Suppose you want to write a program to translate telephone numbers into +letters. A telephone number has seven digits, each of which corresponds to +three letters. How many different strings of letters are possible? Well, +there are three choices for the first digit, times three for the second, and +so on... + +<P>These are typical of the kinds of mathematics problems that a computer + +scientist confronts in that they are <EM>counting</EM> problems--ones that +involve integers. Another relevant kind of problem is the <EM>logic</EM> +problem, in which the values under consideration are just <CODE>true</CODE> and +<CODE>false</CODE>. These areas of mathematics are quite different from what is +studied in the usual high school and college math courses: algebra, +geometry, trig, calculus, differential equations. Those courses deal with +<EM>measurement</EM> problems, in which the answer can be any number, +including a fraction or an irrational number. This conventional mathematics + +curriculum, studying <EM>continuous</EM> functions, is dictated by the needs +of physics and the physics-based engineering subjects. Computer scientists +need a different kind of math, called <EM>discrete</EM> mathematics. +("Discrete" is the opposite of "continuous" and is not the same word as +its homonym "discreet" meaning tactful.) + +<P><H2>Propositional Logic</H2> + +<P>You already know that what in Logo is called an <EM>operation</EM> is the +computer programming version of a mathematical <EM>function.</EM> The inputs +and outputs of Logo operations may be numbers, or they may be other kinds of +words or lists. In ordinary algebra the functions we use have numeric +values. Certain Logo operations are identical to the ones used in algebra: +<CODE>sin :x</CODE> is sin(<EM>x</EM>) and <CODE>sqrt :x</CODE> is √<EM>x</EM>. On the other +hand, there is nothing in ordinary school mathematics quite like <CODE>first</CODE> +or <CODE>sentence</CODE>. You may have been taught to use the word "function" +only when you see a notation like <EM>f</EM>(<EM>x</EM>), but in fact the ordinary +arithmetic operations are functions, too. The addition in <EM>a</EM>+<EM>b</EM> is a +function with two arguments, just like <CODE>sum :a :b</CODE> in Logo. + +<P> + +<P>In Logo there are also operations whose inputs and outputs are the words +<CODE>true</CODE> and <CODE>false</CODE>. The primitive operations in this category are +<CODE>and</CODE>, <CODE>or</CODE>, and <CODE>not</CODE>. Just as algebra deals with numeric +functions, <EM>logic</EM> is the branch of mathematics that deals with these + +<EM>truth-valued</EM> functions. Instead of numbers, these functions combine +<EM>propositions</EM>: statements that may be true or false. A Logo +expression like <CODE>:x=0</CODE> represents a proposition. "Abraham Lincoln was +the King of England" is a proposition; it happens to be false, but it's a +perfectly valid one because it asserts something that's either true or +false. "It will rain in Boston tomorrow" is a proposition whose truth +value we don't know yet. "Chinese food is better than French food" is an +example of a sentence whose validity as a proposition is open to question. +If I say that, I'm expressing my personal taste, not an objective statement +that could be proven true or false.<SUP>*</SUP> + +<P><SMALL><BLOCKQUOTE><SMALL><SUP>*</SUP>On the other hand, "The +Beatles are better than Led Zeppelin" is a perfectly valid, obviously true +proposition.</SMALL></BLOCKQUOTE></SMALL><P>Logical functions combine <EM>simple</EM> propositions into <EM>compound</EM> +propositions. For example, "Either Abraham Lincoln was the King of England +or he was the President of the United States" is a +compound proposition. +It's true even though one of the simple propositions within it is false. +Just as in algebra we use letters like <EM>x</EM> to represent numbers and +expressions like <EM>x</EM>+<EM>y</EM> to indicate the use of functions to combine numbers, +in logic we use letters to represent propositions and there are function +symbols for the logical functions. If <EM>p</EM> is the proposition "Abraham +Lincoln was the King of England," and <EM>q</EM> is the proposition "Abraham +Lincoln was the President of the United States," then the expression <EM>p</EM>∨<EM>q</EM> represents the compound proposition above. The symbol ∨ represents +the <EM>or</EM> function; ∧ +represents <EM>and</EM>; ¬ and ∼ +are alternative representations for <EM>not.</EM> The symbol → represents +"implies"; it turns out that <EM>p</EM>→<EM>q</EM> is equivalent to ¬<EM>p</EM>∨<EM>q</EM>; +in other words, the value of the function is true if either the "if" part +is <EM>false</EM> or the "then" part is true. An example of the former is +the classic "If wishes were horses then beggars would ride." + +<P>(Don't confuse the → function with the Logo <CODE>if</CODE> command. The +latter isn't a function (an operation), but a command. It tells Logo to +take some <EM>action</EM> if a given condition is met. The operation + +<P><PRE>to implies :p :q +output or (not :p) :q +end +</PRE> + +<P>is the Logo equivalent of the → function in logic.) + +<P>The most important use of logic in mathematics is in understanding the idea +of <EM>proof.</EM> What is a valid reason for claiming that some proposition +has been proven true? Many people come across the idea of proof for the +first and last time in high school geometry. We are asked to prove some +proposition like "the sum of the interior angles of a triangle is +180°." For each step in the proof we must give a <EM>reason</EM> +such as "things equal to the same thing are equal to each other." + +<P>In logic there are certain rules that allow us to infer one proposition from +one or more previously known propositions. These rules correspond +roughly to the "reasons" in a geometry proof. They are called +<EM>rules of inference.</EM> You use rules of +inference informally all the time, whenever +you try to convince someone of something by reasoning. "Is Jay here?" +"Yes." "How do you know?" "I saw his car in the driveway, and if his car +is here, he must be here too." + +<P>Suppose we use the letter <EM>p</EM> to represent the proposition "Jay's car is +here" and the letter <EM>q</EM> to represent "Jay is here." Then the reasoning +quoted in the last paragraph says "<EM>p</EM> is true and <EM>p</EM>→<EM>q</EM> is true, so +<EM>q</EM> must be true." ("<EM>p</EM>→<EM>q</EM>" is the proposition "If Jay's car is +here, he must be here too.") The fact that <EM>p</EM> and <EM>p</EM>→<EM>q</EM> allow us to +infer <EM>q</EM> is a rule of inference. (Of course the rule doesn't +tell us about the truth of its component propositions. We have to determine +that by some means outside of logic, such as observation of the world. +I had to <EM>see</EM> Jay's car in the driveway to know that <EM>p</EM> is true.) + +<P><H2>An Inference System</H2> + +<P>What does all this have to do with computer science? One application of +logic is in <EM>inference systems</EM>: programs that deduce propositions +from other ones. Such systems are important both in business applications +where large data bases are used and in artificial intelligence programs that +try to answer questions based on information implied by some text but not +explicit in the text. + +<P>In this section I'll show you a special-purpose inference system that solves +logic problems. Logic problems are the ones in which you're given +certain propositions and asked to deduce others. Mr. Smith lives next to +the carpenter; John likes classical music; who lives in the yellow house? +Here is a typical problem taken from <EM>Mind Benders,</EM> Book B-2, +by Anita Harnadek. + +<P><BLOCKQUOTE> +<P><A NAME="harnadek">A cub reporter +interviewed four people. He was very careless, however. +Each statement he wrote was half right and half wrong. He went back and +interviewed the people again. And again, each statement he wrote was half +right and half wrong. From the information below, can you straighten out +the mess? + +<P>The first names were Jane, Larry, Opal, and Perry. The last names were +Irving, King, Mendle, and Nathan. The ages were 32, 38, 45, and 55. The +occupations were drafter, pilot, police sergeant, and test car driver. + +<P>On the first interview, he wrote these statements, one from each person: + +<P><P> + +<P><TABLE><TR><TH align="right" valign="top">1.<TD> <TD valign="top"> Jane: "My name is Irving, and I'm 45." +<TR><TH align="right" valign="top">2.<TD> <TD valign="top"> King: "I'm Perry and I drive test cars." +<TR><TH align="right" valign="top">3.<TD> <TD valign="top"> Larry: "I'm a police sergeant and I'm 45." +<TR><TH align="right" valign="top">4.<TD> <TD valign="top"> Nathan: "I'm a drafter, and I'm 38." + +<P></TABLE> + +<P>On the second interview, he wrote these statements, one from each person: + +<P><P> + +<P><TABLE><TR><TH align="right" valign="top">5.<TD> <TD valign="top"> Mendle: "I'm a pilot, and my name is Larry." +<TR><TH align="right" valign="top">6.<TD> <TD valign="top"> Jane: "I'm a pilot, and I'm 45." +<TR><TH align="right" valign="top">7.<TD> <TD valign="top"> Opal: "I'm 55 and I drive test cars." +<TR><TH align="right" valign="top">8.<TD> <TD valign="top"> Nathan: "I'm 38 and I drive test cars." + +<P></TABLE></BLOCKQUOTE> + +<P> +<CENTER><IMG SRC="grid.gif" ALT="figure: grid"></CENTER> + + +<P>The chart provided with the problem is a guide to its solution. Each square +in the chart represents a proposition. For example, the box where the +"Larry" row meets the "pilot" column represents the proposition "Larry +is the pilot." In solving the problem, you can put marks in the boxes to +indicate what you know about the propositions. The status of a proposition +need not be only true or false. Initially the status of each proposition is +<EM>unknown</EM>; we have no idea whether it's true or false. The structure +of this particular problem also allows the status of a proposition to be that +it is linked with another proposition in an <EM>exclusive-or</EM> +relationship; that is, if one of the linked propositions turns out to be +true, then the other must be false, and vice versa. You can use whatever +notation you find convenient to express these possibilities. After +experimenting with T and F and with check marks and crosses, I found that +circles for true propositions and crosses for false ones made it easiest for +me to see quickly the pattern of known truths. For the linked propositions, +I used the statement numbers (1 to 8) in the boxes; two boxes with the same +number represent linked statements. + +<P>You should probably solve this problem by hand before we go on to discuss +the computer solution. Stop reading now and work on the problem if you want +to do it without any hints from me. + +<P>Let me introduce a little new terminology to help in the following +discussion. I'll call something like "last name" or "occupation" a +<EM>category</EM>; something like "Mendle" or "pilot" I'll call an +<EM>individual.</EM> As I'm using this terminology, "Mendle" and "pilot" +are two different individuals even if they turn out, when we solve the +problem, to be the same person. + +<P>It's important that each group of four statements contains one from each +person, because the names of the speakers include first and last names. +That is, from the first group of statements we know that Jane, King, Larry, +and Nathan are four distinct people. This falsifies such propositions as +"Jane is King." After noting the first group of statements my chart looks +like this: + +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/grid2.gif" ALT="figure: grid2"></CENTER> + +<P>From the second group of statements we learn that Mendle, Jane, Opal, and +Nathan are all distinct people. When I marked an X in the "Jane is +Mendle" box, I noticed that all but one last name for Jane had been +eliminated. I therefore put a circle in the "Jane is Irving" box. This +illustrates a special rule of inference for problems of this kind: If, for +a given individual <EM>x</EM>, all but one proposition "<EM>x</EM> is <EM>y</EM>" have been +falsified for a certain <EM>category</EM> of <EM>y</EM> individuals, then the +remaining proposition in that category must be true. (The reason I'm going +through this analysis is that the rules of inference I discover while +working the problem by hand are going to end up in the design of the +computer program.) I'm going to call this the <EM>elimination</EM> rule. + + +<P>Since Jane is Irving, nobody else can be Irving. This falsifies three +propositions whose status was formerly unknown: "Larry is Irving," +"Opal is Irving," and "Perry is Irving." (The truth of "Jane is Irving" +would also falsify "Jane is King" and so on, but we already knew those to +be false.) The general rule is that if "<EM>x</EM> is <EM>y</EM>" is true then "<EM>x</EM> is +<EM>z</EM>" must be false for all other <EM>z</EM> in the same category as <EM>y</EM>, and +likewise "<EM>w</EM> is <EM>y</EM>" is false for all other <EM>w</EM> in the same category as +<EM>x</EM>. I'll call this the <EM>uniqueness</EM> rule. + + +<P>The proposition "Jane is Irving" was linked with the proposition +"Jane is 45" earlier. That latter proposition must therefore be false. +This is another rule of inference, the <EM>link falsification</EM> rule. +There is also a <EM>link verification</EM> rule that comes into play when a +linked proposition is found to be false; the other linked proposition must +then be true. + +<P>Since we know that "Jane is 45" is false, and that "Jane is Irving" is +true, it follows that "Irving is 45" must be false. The general rule is +that if "<EM>x</EM> is <EM>y</EM>" is true and "<EM>x</EM> is <EM>z</EM>" is false, then "<EM>y</EM> is +<EM>z</EM>" must also be false. Similarly, if "<EM>x</EM> is <EM>y</EM>" is true and "<EM>x</EM> is +<EM>z</EM>" is true, then "<EM>y</EM> is <EM>z</EM>" must be true. I'll call these the +<EM>transitive</EM> rules. + + +<P>You should be following along with your own copy of the chart. By the +elimination rule, "Opal is King" must be true. Then, by the uniqueness +rule, "Perry is King" is false. Then, by the link verification rule, +"King is test driver" must be true. By the transitive rule, "Opal is +test driver" is true also. Here is my chart after making all possible +deductions from the fact that Mendle, Jane, Opal, and Nathan are distinct +people: + +<P><CENTER><IMG SRC="grid3.gif" ALT="figure: grid3"></CENTER> + +<P>Looking at statement number 5, we see that "Mendle is pilot" is linked to +"Mendle is Larry." But we already know that the latter is true, so the +former must be false. We can just put an X in that box and not bother +marking the number 5 anywhere. The same is true for statements 6 and 7; +here's my chart after statement 7: + +<P> +<CENTER><IMG SRC="grid4.gif" ALT="figure: grid4"></CENTER> + +<P>I haven't marked anything in the +age vs. occupation section of the chart, even though I can deduce some +propositions for that section. For example, I know that "Jane is pilot" +is true and that "Jane is 45" is false. By the transitive rule, "pilot +is 45" must be false. I just haven't bothered making <EM>all</EM> possible +deductions; I can always fill in that section of the chart if I get to the +end of the problem and still don't know who's who. + +<P>Before dealing with the final statement we know all the pairings of first +and last names, but we don't know any ages and we only know half the jobs. +The last statement lets loose a flurry of deductions. The critical one is +that if Nathan is 38, he or she (Perry is an ambiguous first name) can't be +the drafter because of the link from statement 4. Here is my final chart: + +<P><CENTER><IMG SRC="grid5.gif" ALT="figure: grid5"></CENTER> + +<P>Once it was clear that I was in the final steps of the solution, I +didn't bother maintaining the age vs. last name section. The results can +be found by reading just the three sections at the top; for example, +Jane is Irving, the pilot, and 55. + +<P><H2>Problems with Ordering</H2> + +<P>The elimination, uniqueness, and transitive rules are useful in just about +all logic problems, but the link falsification and link verification rules +depend on this specific problem's gimmick that we are given pairs of +propositions and told that exactly one of them is true. To solve other +problems, a more flexible kind of linkage is needed; we must be able to say +"if <EM>p</EM> is true, then <EM>q</EM> is true also" or "if <EM>p</EM> is false, then <EM>q</EM> +must be true," and so on. + +<P>A very common kind of linkage is an <EM>ordering,</EM> in which we are +told a sequence of events, or a row of houses on a street, for example. +In the cub reporter problem, the ages form an ordering, but aren't used +as such--that is, the problem doesn't include clues such as "the test +driver is younger than Jane." Suppose we did see that clue; what could +we conclude from it? Certain propositions would be settled for sure: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top">The test driver must not be Jane. +<TR><TH align="right" valign="top">•<TD> <TD valign="top">The test driver isn't the oldest age (55). +<TR><TH align="right" valign="top">•<TD> <TD valign="top">Jane isn't the youngest age (32). +</TABLE><P> + +<P>Other propositions would be linked by <EM>implications:</EM> + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Jane is 38, <STRONG>then</STRONG> the driver is 32. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Jane is 45, <STRONG>then</STRONG> the driver is 32 or 38. +</TABLE><P> + +<P>and so on. (Actually, the second of these isn't directly +representable on the chart, because there's no notation for a single +proposition with two alternatives, like "32 or 38." So instead +we'd represent this using propositions about what <EM>can't</EM> be +true: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Jane is 45, <STRONG>then</STRONG> the driver is not 55. +</TABLE><P> + +<P>We already know that the driver isn't Jane, so there's no need +to record the implication that if Jane is 45 the driver isn't 45.) + +<P>Here is another problem, called "Forgetful Footes," +by Diane C. Baldwin. +It is taken from <EM>The Dell Book of Logic Problems #4.</EM> + +<P><BLOCKQUOTE> + +<P><A NAME="baldwin">The forgetful Foote</A> family +fairly flew from their flat up Fleet Street +to the freeway for a fling in Florida. Before they passed five +intersections, Felix and the other four Footes found they each had forgotten +something (including the food) and were forced back to their flat to fetch +it. Each turnaround was made at a different street intersection, one of +them at Field Street. From the following clues, can you figure out who +forgot what and in what order, and find the order of the intersections on +Fleet Street from the Foote's flat to the freeway? + +<P><P> + +<P><TABLE><TR><TH align="right" valign="top">1.<TD> <TD valign="top"> The second turnaround began at the street following Flag Street and +the street before Fred had to return to the flat. +<TR><TH align="right" valign="top">2.<TD> <TD valign="top"> The men were responsible for the return for the film, the +turnaround at Fig Street, and the fifth trip back. +<TR><TH align="right" valign="top">3.<TD> <TD valign="top"> Fork Street followed the one where they returned to fetch the +flashlight and preceded the one where a woman had them make their first +turnaround. +<TR><TH align="right" valign="top">4.<TD> <TD valign="top"> The final trip back didn't begin at Frond Street, nor was it the +one to fetch the fan. +<TR><TH align="right" valign="top">5.<TD> <TD valign="top"> Frank's forgetfulness turned them back one block and one return +trip following Francine's. +<TR><TH align="right" valign="top">6.<TD> <TD valign="top"> One woman was the third to forget, while the other woman turned +them back at Flag Street. +<TR><TH align="right" valign="top">7.<TD> <TD valign="top"> They returned for the fiddle just before the trip back that began +at Frond Street and just following the one requested by Flo. + +<P></TABLE></BLOCKQUOTE><P> + +<P>This problem includes <EM>two</EM> orderings. The order of the intersections +with cross streets is not necessarily the same as the time order of the +return trips. That is, the Footes might have gone four blocks before making +their first turnaround, then gone only one block before the second return, +and so on. In making a chart for this problem, I used the numbers 1-5 to +represent the order of streets, and the ordinals 1st-5th to represent the +time order of return trips. Clue 1, then, gives us this series of +implications: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Flag Street is 1, <STRONG>then</STRONG> 2nd is 2. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Flag Street is 2, <STRONG>then</STRONG> 2nd is 3. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Flag Street is 3, <STRONG>then</STRONG> 2nd is 4. +<P> +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 2, <STRONG>then</STRONG> Flag Street is 1. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 3, <STRONG>then</STRONG> Flag Street is 2. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 4, <STRONG>then</STRONG> Flag Street is 3. +<P> +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 2, <STRONG>then</STRONG> Fred is 3. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 3, <STRONG>then</STRONG> Fred is 4. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> 2nd is 4, <STRONG>then</STRONG> Fred is 5. +<P> +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Fred is 3, <STRONG>then</STRONG> 2nd is 2. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Fred is 3, <STRONG>then</STRONG> 2nd is 3. +<TR><TH align="right" valign="top">•<TD> <TD valign="top"><STRONG>If</STRONG> Fred is 5, <STRONG>then</STRONG> 2nd is 4. + +<P></TABLE><P> + +<P>It may seem that there are some missing from this list. What if +Flag Street is 4? But that can't happen (and I so marked the chart) because +then 2nd would have to be 5, and that would make Fred 6, which is too far. +But notice that we do have to include both directions of implication between +any two propositions. The clue tells us that if Flag Street is 1, then 2nd +is 2, and also that if 2nd is 2, then Flag Street is 1. + +<P>See if you can solve this problem, and then we'll talk about the +Logo-based inference system. + +<P><H2>Data Structure</H2> + +<P>In addition to the status of the "<EM>x</EM> is <EM>y</EM>" propositions, the program +needs to keep track of the categories, like "first name," and the +individuals within each category. This information is needed for the sake +of the elimination and uniqueness rules. I chose to have a global variable +named <CODE>categories</CODE> containing (for the cub reporter problem) the list + +<P><PRE>[first last age job] +</PRE> + +<P>Each of the elements of that list is the name of a variable +containing the individuals in that category; for example, <CODE>:age</CODE> is +the list + +<P><PRE>[32 38 45 55] +</PRE> + +<P>The status of the "is" propositions is kept in property lists associated +with the names of individuals. For example, to indicate that the proposition +"Jane is King" is false, the program carries out these two instructions: + +<P><PRE>pprop "Jane "King "false +pprop "King "Jane "false +</PRE> + +<P>Both are necessary because we can't predict whether we're going +to be figuring out something about Jane or something about King when we +next need this information. Actually, the fact that the proposition is +stored twice reflects another inference rule, one that's so obvious we +don't think about it at all when solving these problems without using a +computer: the <EM>symmetric</EM> rule says that if <EM>x</EM> is <EM>y</EM>, then +<EM>y</EM> is <EM>x</EM>. + +<P>If a given property's value is the empty list, that means that the truth of +the proposition is unknown. (Remember that Logo property lists give the +empty list as the value of a property that you haven't defined explicitly, +so I don't have to predefine all possible properties.) The word <CODE>true</CODE> +means that the proposition is known to be true; the word <CODE>false</CODE> means +that it's known to be false. If the proposition is linked to other +propositions by implication, then the value of the property is a list +containing four-element implication lists. The first member of each +implication is <CODE>true</CODE> or <CODE>false</CODE> to indicate which value of this +proposition implies something about the other proposition. The next two +members are names of individuals, indicating which other proposition is +determined by this one. The fourth member is again <CODE>true</CODE> or <CODE> +false</CODE>, indicating whether that other proposition is implied to be true +or implied to be false. + +<P>For example, the +statement "My name is Irving, and I'm 45" attributed to Jane is stored as +the following two implications: + +<P><P> +<TABLE><TR><TH align="right" valign="top">•<TD> <TD valign="top">Under <CODE>Jane</CODE> and <CODE>Irving</CODE>, the list <CODE>[true Jane 45 false]</CODE>. +<TR><TH align="right" valign="top">•<TD> <TD valign="top">Under <CODE>Jane</CODE> and <CODE>45</CODE>, the list <CODE>[true Jane Irving false]</CODE>. +</TABLE><P> + +<P>Although the data structure as described so far +contains all the necessary information, it +turned out to be convenient to include some redundant forms of the same +information. For example, the elimination rule and the uniqueness rule +require the program to find all the <EM>peers</EM> of an individual--the +other individuals in the same category. It would be possible to start with +<CODE>:categories</CODE> and search for the known individual in a category list, +but it was easier to give each individual a <CODE>category</CODE> property whose +value is the name of the category to which it belongs. + +<P>Similarly, the transitive rule needs to know all of the propositions +involving a particular individual that are known to be true, and all +those that are known to be false. This +information is implicit in the properties already described, but to simplify +the program each individual has a <CODE>true</CODE> property whose value is a list +of the other individuals known to be equal to this one, and a <CODE>false</CODE> +property whose value is a list of the others known to be different from +this one. For example, after +processing statement 7 we know that Jane is Irving and that Jane is the +pilot, but we don't know Jane's age. Therefore the property list for <CODE> +Jane</CODE> has a property whose name is <CODE>true</CODE> and whose value is the list + +<P><PRE>[Irving pilot] +</PRE> + +<P>and one whose name is <CODE>false</CODE> and whose value is + +<P><PRE>[King Mendle Nathan drafter sergeant driver] + +</PRE> + +<P>Finally, it turned out that at the end of the program, in order to print out +the solutions, it was convenient to have, for each individual, properties +with a category as the name and an individual in that category as the value. +For example, since Jane's last name is Irving, <CODE>Jane</CODE> has a property +whose name is <CODE>last</CODE> and whose value is <CODE>Irving</CODE>. + +<P><H2>Program Structure: Recording Simple Propositions</H2> + +<P>I wanted to enter the problem as a series of assertions, each represented by +a Logo instruction. That is, I wrote this procedure: + +<P><PRE>to cub.reporter +cleanup +category "first [Jane Larry Opal Perry] +category "last [Irving King Mendle Nathan] +category "age [32 38 45 55] +category "job [drafter pilot sergeant driver] +differ [Jane King Larry Nathan] +says "Jane "Irving 45 +says "King "Perry "driver +says "Larry "sergeant 45 +says "Nathan "drafter 38 +differ [Mendle Jane Opal Nathan] +says "Mendle "pilot "Larry +says "Jane "pilot 45 +says "Opal 55 "driver +says "Nathan 38 "driver +print [] +solution +end +</PRE> + +<P>(The first instruction erases any old property lists left over +from a previous logic problem; the last prints out the results.) I made <CODE> +category</CODE>, <CODE>differ</CODE>, and <CODE>says</CODE> print out their inputs when invoked, +so that you can watch the progress of the solution while it's being computed. + +<P>The procedures <CODE>differ</CODE> and <CODE>says</CODE> were designed to reflect the +terms in which this problem is presented, rather than the internal workings +of the inference system. That is, if you compare the problem statement with +this procedure, it's easy to see which instructions represent which clues, +even if you have no idea how the program will actually solve the problem! +Our task is to implement <CODE>differ</CODE> and <CODE>says</CODE> using propositional +logic. + +<P>There's an important difference between <CODE>differ</CODE> and <CODE>says</CODE>. <CODE> +Differ</CODE> gives us direct information about the truth or falsehood of some +simple propositions; specifically, we learn that several "<EM>x</EM> is <EM>y</EM>" +propositions are false. <CODE>Says</CODE>, on the other hand, gives us no +direct information about simple propositions; it tells us about +implications linking two such propositions. + +<P>First let's consider how <CODE>differ</CODE> works. The instruction + +<P> + +<P><PRE>differ [Jane King Larry Nathan] +</PRE> + +<P>tells us that Jane is not King, Jane is not Larry, Jane is +not Nathan, King is not Larry, King is not Nathan, and Larry is not Nathan. +In effect, <CODE>differ</CODE> will carry out the instructions + +<P><PRE>falsify "Jane "King +falsify "Jane "Larry +falsify "Jane "Nathan +falsify "King "Larry +falsify "King "Nathan +falsify "Larry "Nathan +</PRE> + +<P>There's no need to invoke <CODE>falsify</CODE> for the six cases with +inputs in the opposite order (such as the proposition that King is not Jane) +because, as we'll see, <CODE>falsify</CODE> knows about the symmetric rule and +will record those automatically. By the way, some of these six are +unnecessary because the two individuals have the same category and therefore +couldn't possibly be the same, such as Jane and Larry, both first names. +But <CODE>falsify</CODE> will catch these cases and return without doing anything. + +<P>Here's how <CODE>differ</CODE> actually carries out all those <CODE>falsify</CODE> +instructions: + +<P><PRE>to differ :list +print (list "differ :list) +foreach :list [differ1 ? ?rest] +end + +to differ1 :a :them +foreach :them [falsify :a ?] +end +</PRE> + +<P><CODE>Falsify</CODE>, and a similar procedure <CODE>verify</CODE> to assert the truth +of a proposition, are implemented in terms of the central procedure +about propositions, <CODE>settruth</CODE>: + +<P><PRE>to verify :a :b +settruth :a :b "true +end + +to falsify :a :b +settruth :a :b "false +end +</PRE> + +<P><CODE>Settruth</CODE> takes three inputs, two individuals and a truth +value. It records the truth or falsehood of the proposition that <CODE>:a</CODE> +is <CODE>:b</CODE>, and uses the rules of inference I've described to derive +other propositions when possible. + +<P><PRE>to settruth :a :b :truth.value +if equalp (gprop :a "category) (gprop :b "category) [stop] +localmake "oldvalue get :a :b +if equalp :oldvalue :truth.value [stop] +if equalp :oldvalue (not :truth.value) ~ + [(throw "error (sentence [inconsistency in settruth] + :a :b :truth.value))] +print (list :a :b "-> :truth.value) +store :a :b :truth.value +settruth1 :a :b :truth.value +settruth1 :b :a :truth.value +if not emptyp :oldvalue ~ + [foreach (filter [equalp first ? :truth.value] :oldvalue) + [apply "settruth butfirst ?]] +end + +to settruth1 :a :b :truth.value +apply (word "find not :truth.value) (list :a :b) +foreach (gprop :a "true) [settruth ? :b :truth.value] +if :truth.value [foreach (gprop :a "false) [falsify ? :b] + pprop :a (gprop :b "category) :b] +pprop :a :truth.value (fput :b gprop :a :truth.value) +end +</PRE> + +<P>If the two individuals are in the same category, <CODE>settruth</CODE> +does nothing. This is to allow for cases such as the example + +<P><PRE>falsify "Jane "Larry +</PRE> + +<P>as explained earlier. If the individuals are in different +categories, the next step is to find what information was previously +available about this proposition. If it was already known to be true +or false, and the truth value input in this call agrees with what was +known, then the program has merely generated some redundant information +and <CODE>settruth</CODE> stops. If the known value disagrees with the input +value, then something is wrong; the program has proven two contradictory +propositions. Generally this means that some clue has been represented +incorrectly in the program. + +<P>If the proposition was not already known to be true or false, then we +have some new information. After notifying the user by printing a +message, <CODE>settruth</CODE> +must store that fact. (Procedures <CODE>get</CODE> and <CODE>store</CODE> are an +interface to the property list primitives that implement the symmetric +rule.) The next step is to make any possible inferences using the +elimination, uniqueness, and transitive rules; this is done separately +for "<CODE>:a</CODE> is <CODE>:b</CODE>" and for "<CODE>:b</CODE> is <CODE>:a</CODE>" by two +calls to the subprocedure <CODE>settruth1</CODE>. + +<P><CODE>Settruth1</CODE> invokes either <CODE>findtrue</CODE> or <CODE>findfalse</CODE> +depending on the truth value. Because of the <CODE>not</CODE> in the +first instruction of <CODE>settruth1</CODE>, <CODE>findtrue</CODE> is called when we are +falsifying a proposition, and vice versa. This makes sense because of +the tasks of these procedures. If we are falsifying a proposition, +then the elimination rule comes into play, and we try to find a true +proposition. If we are verifying a proposition, then the uniqueness +rule lets us find several false propositions on the same row or +column of the chart. The next instructions in <CODE>settruth1</CODE> implement +the transitive rule, looking at other individuals known to be the same +as, or different from, <CODE>:a</CODE>. The last two instructions maintain +the redundant information used for printing the results and for carrying +out the transitive rule. + +<P>The final instruction in <CODE>settruth</CODE> deals with implications. If we +already knew that <EM>p</EM>→<EM>q</EM> and now we're learning that <EM>p</EM> is true, +we can infer that <EM>q</EM> is true. (This is another rule of inference, +which I'll call the <EM>implication</EM> rule.) + +<P><H2>Program Structure: Recording Implications</H2> + +<P>Speaking of implications, we can now explore how the <CODE>says</CODE> procedure +produces and records implications. The instruction + +<P><PRE>says "Jane "Irving 45 +</PRE> + +<P>establishes a relationship between the two propositions +"Jane is Irving" and "Jane is 45." The relationship is that +exactly one of them must be true; the name for this is <EM>exclusive or.</EM> + +<P><PRE>to says :who :what1 :what2 +print (list "says :who :what1 :what2) +xor :who :what1 :who :what2 +end + +to xor :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "false +implies :who1 :what1 "false :who2 :what2 "true +end +</PRE> + +<P><CODE>Says</CODE> is a special case of <CODE>xor</CODE> (a common abbreviation +for exclusive or) in which the two propositions are about a common +individual, Jane in the example. The <CODE>xor</CODE> procedure establishes +two implications, <EM>p</EM> → ¬  <EM>q</EM> and +¬  <EM>p</EM> → <EM>q</EM>. In other words, +if we learn that Jane is Irving, then we can infer that Jane is not 45; +if we learn that Jane is not Irving, we can infer that Jane is 45. +(These two implications are <EM>not</EM> equivalent to each other; in +general, one +might be true and the other false. But the exclusive or relationship +means that both are true.) + +<P>The <CODE>implies</CODE> procedure takes six inputs. The first three are for +one proposition and the others for the second proposition. For each +proposition, two inputs are individuals (call them <EM>x</EM> and <EM>y</EM>) and +the third is <CODE>true</CODE> or <CODE>false</CODE>. If <CODE>true</CODE>, then the +proposition is "<EM>x</EM> is <EM>y</EM>"; if <CODE>false</CODE>, the proposition is +"<EM>x</EM> is not <EM>y</EM>." + +<P>Yet another rule of inference comes into play here, the <EM> +contrapositive</EM> rule. It says +that if <EM>p</EM>→<EM>q</EM> is true, then so is ¬<EM>q</EM> → ¬<EM>p</EM>. +Although these two implications are mathematically equivalent, +we must enter both of them into our data structure because we might +happen to discover that ¬<EM>q</EM> is true, and we'll look for relevant +implications filed under <EM>q</EM> rather than under <EM>p</EM>. + +<P><PRE>to implies :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who2 :what2 (not :truth2) :who1 :what1 (not :truth1) +end +</PRE> + +<P>The first call to <CODE>implies1</CODE> stores the implication +in the form given to us; the second call stores its contrapositive. + +<P><PRE>to implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +localmake "old1 get :who1 :what1 +if equalp :old1 :truth1 [settruth :who2 :what2 :truth2 stop] +if equalp :old1 (not :truth1) [stop] +if memberp (list :truth1 :who2 :what2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +if memberp (list :truth1 :what2 :who2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +store :who1 :what1 ~ + fput (list :truth1 :who2 :what2 :truth2) :old1 +end +</PRE> + +<P>The first three instructions in <CODE>implies1</CODE> check for the +case in which we are told that <EM>p</EM>→<EM>q</EM> but we already know +either <EM>p</EM> or ¬<EM>p</EM>. If we already know <EM>p</EM>, then we can +derive that <EM>q</EM> is true. There's no need to store the implication, +because it is already serving its purpose, which is to allow us to +infer <EM>q</EM>. If we already know ¬<EM>p</EM>, then we can forget about +this implication, because it isn't going to do us any good. We can't +infer anything about <EM>q</EM> from this situation. + +<P>The next two instructions check for the situation in which we +are told <EM>p</EM>→<EM>q</EM> but we already know that <EM>p</EM>→¬<EM>q</EM>. +In that case, <EM>p</EM> must not be true, because if it were, we could +infer two contradictory conclusions. Therefore, we can falsify +the proposition <EM>p</EM>. + +<P>Finally, if none of these conditions is met, we add this implication +to the (possibly empty) list of already known implications about <EM>p</EM>. + +<P><H2>Using Implications to Represent Orderings</H2> + +<P>For another example of implications at work, here's the Logo program +for the Foote problem: + +<P><PRE>to foote.family +cleanup +category "when [1st 2nd 3rd 4th 5th] +category "name [Felix Fred Frank Francine Flo] +category "street [Field Flag Fig Fork Frond] +category "item [food film flashlight fan fiddle] +category "position [1 2 3 4 5] +print [Clue 1] +justbefore "Flag "2nd :position +justbefore "2nd "Fred :position +print [Clue 2] +male [film Fig 5th] +print [Clue 3] +justbefore "flashlight "Fork :position +justbefore "Fork "1st :position +female [1st] +print [Clue 4] +falsify "5th "Frond +falsify "5th "fan +print [Clue 5] +justbefore "Francine "Frank :position +justbefore "Francine "Frank :when +print [Clue 6] +female [3rd Flag] +print [Clue 7] +justbefore "fiddle "Frond :when +justbefore "Flo "fiddle :when +print [] +solution +end +</PRE> + +<P> +I've included <CODE>print</CODE> instructions to let the user know when the +program reaches each of the seven numbered clues. Clue 4 tells us +directly that two possible pairings of individuals are false, and +the program reflects this with two invocations of <CODE>falsify</CODE>. But +the other clues either tell us about the sex of the family members +or tell us that certain individuals are next to each other in an +ordering. The procedures <CODE>male</CODE>, <CODE>female</CODE>, and <CODE>justbefore</CODE> +reflect the language of the problem in the same way that <CODE>says</CODE> +reflected the language of the other problem. + +<P><PRE>to male :stuff +differ sentence :stuff [Francine Flo] +end + +to female :stuff +differ sentence :stuff [Felix Fred Frank] +end +</PRE> + +<P>Needless to say, this implementation of <CODE>male</CODE> and <CODE>female</CODE> +works only for this specific logic problem! It's tempting to try to +use the more general category mechanism this way: + +<P><PRE>category "sex [male female] +verify "Francine "female +verify "Flo "female +verify "Felix "male +verify "Fred "male +verify "Frank "male +</PRE> + +<P>but unfortunately the structure of this inference system +requires that each individual can only match one individual in +another category; once we've verified that Francine is female, +the uniqueness rule will deduce that Flo isn't female! + +<P>On the other hand, I've tried to write <CODE>justbefore</CODE> in a way +that will work for future problems. + +<P><PRE>to justbefore :this :that :lineup +falsify :this :that +falsify :this last :lineup +falsify :that first :lineup +justbefore1 :this :that :lineup +end + +to justbefore1 :this :that :slotlist +if emptyp butfirst :slotlist [stop] +equiv :this (first :slotlist) :that (first butfirst :slotlist) +justbefore1 :this :that (butfirst :slotlist) +end + +to equiv :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "true +implies :who2 :what2 "true :who1 :what1 "true +end +</PRE> + +<P>The input named <CODE>lineup</CODE> is a list of individuals from +an ordering, in the correct order. In this problem, it will be the list + +<P><PRE>[1 2 3 4 5] +</PRE> + +<P>if the clue is about street position, or + +<P><PRE>[1st 2nd 3rd 4th 5th] +</PRE> + +<P>if the clue is about the order of events in time. As I explained +when talking about orderings earlier, the instruction + +<P><PRE>justbefore "Flag "2nd :position +</PRE> + +<P>results in falsifying some propositions: + +<P><PRE>falsify "Flag "2nd +falsify "Flag 5 +falsify "2nd 1 +</PRE> + +<P>and also asserts some implications: + +<P><PRE>implies "Flag 1 "true "2nd 2 "true +implies "2nd 2 "true "Flag 1 "true +implies "Flag 2 "true "2nd 3 "true +implies "2nd 3 "true "Flag 2 "true +implies "Flag 3 "true "2nd 4 "true +implies "2nd 4 "true "Flag 3 "true +implies "Flag 4 "true "2nd 5 "true +implies "2nd 5 "true "Flag 4 "true +</PRE> + +<P><H2>Backtracking</H2> + +<P>This inference system can solve many logic problems, but sometimes it +runs into trouble. I've already mentioned, while discussing the <CODE>male</CODE> +and <CODE>female</CODE> procedures, that the program insists that each individual +in a category must appear exactly once in the solution. Suppose you have +a problem about five people living in five houses; they have five distinct +first names, five last names, five occupations--but two of the houses +are yellow. It's sometimes possible to get around this, but the technique +is a little awkward. You can set up a category like this: + +<P><PRE>category "color [yellow1 yellow2 blue brown green] +</PRE> + +<P>then you find <EM>one</EM> clue that mentions a yellow house +and use <CODE>yellow1</CODE> for that one: + +<P><PRE>verify "Fred "yellow1 +</PRE> + +<P>but for any other mention of something being yellow in the +problem, you represent that by saying that the individual is <EM>not</EM> one +of the other colors: + +<P><PRE>differ "architect [blue brown green] +</PRE> + +<P>You never explicitly mention <CODE>yellow2</CODE> except in setting +up the category. + +<P>That technique works if you know that yellow is the color that appears +twice. What if the problem tells you only that there are five houses +and four colors? Or what if some individuals are <EM>not</EM> in the +solution? For example, a problem might discuss the activities of five +people, each doing something on a different day of the week, but you +don't know until you solve the problem which of the seven weekdays +are involved. + +<P>An entirely different approach to solving logic problems by computer +is <EM>backtracking.</EM> Instead of starting from the clues +and making deductions, a program can start by making arbitrary guesses +about who goes with what, and then use the clues to look for contradictions. +If a contradiction is found, the program systematically makes a different +guess until every possible arrangement has been tried. (Presumably before +every possibility has been tried, one of them will <EM>not</EM> lead to a +contradiction, and that's the solution.) + +<P>In practice, backtracking is a more flexible technique than the inference +system I wrote, because it's easy to let a backtracking program try +multiple appearances of an individual if the problem allows that. But I +thought the inference system would be more interesting to study, for two +reasons. First, the inference system more closely models the way people +solve logic problems. In the cub reporter problem, with four people +to keep straight, there are (4!)<SUP><SMALL>3</SMALL></SUP> or 13,824 possible solutions. In +the Foote problem, with five people, there are (5!)<SUP><SMALL>4</SMALL></SUP> or just over +200 million possibilities. A computer can try them all, but a person +couldn't.<SUP>*</SUP> +(If multiple appearances were allowed, the numbers would be +even higher.) Second, backtracking doesn't work at all unless the problem +deals with a finite set of individuals, as in a logic problem. Inference +systems can be generalized to deal with potentially unbounded problems. + +<P><SMALL><BLOCKQUOTE><SMALL><SUP>*</SUP>People do sometimes use a combination of inference and +backtracking. If, by inference, you've established that Jane must be +either the pilot or the drafter, but you can't settle which, you might +decide to <EM>assume</EM> that Jane is the pilot and hope that you can then +infer either a complete solution to the problem or a contradiction. In the +latter case, you'd know that Jane must be the drafter.</SMALL></BLOCKQUOTE></SMALL><P><H2>Generalized Inference Systems and Predicate Logic</H2> + +<P>The rules of inference in this program are specially designed for problems +like the ones we've just solved. The implication +rule is applicable to any propositional logic situation, but the ones +based on categories, such as the uniqueness and elimination rules, are not. +The idea of a "category" as we've used it +isn't a general principle of logic; instead, that idea should really be +expressed as a series of propositions. For example, to say "there is a +category called `last name' whose members are Irving, King, Mendle, and +Nathan" is really to make several statements of the form "Jane has exactly +one last name," or, in terms of the basic "<EM>x</EM> is <EM>y</EM>" propositions, +<P><CENTER><TABLE><TR><TD>(Jane is Irving) ∨ (Jane is King) +<TR><TD> ∨ (Jane is Mendle) ∨ (Jane is Nathan) +</TABLE></CENTER><P> +and so on. If we wanted to solve this problem in a general +inference system we'd assert the truth of all those propositions at the +beginning. Then if the program discovers that Jane is Irving, it would +have the two propositions +<P><CENTER>¬<STRONG>(</STRONG>(Jane is Irving) +∧ (Jane is King)<STRONG>)</STRONG></CENTER><P> +and +<P><CENTER>(Jane is Irving)</CENTER><P> +and from these it could infer +<P><CENTER>¬(Jane is King)</CENTER><P> +using the standard inference rules of propositional logic. + +<P>The "and so on" just above includes quite a large number of propositions. +And yet this small problem concerns a mere 16 individual names divided into +four categories. For a larger problem it would be nearly impossible to list +all the relevant propositions, and for a problem involving an infinite set +of individuals, such as the integers, it would be literally impossible. What +would make the representation of a problem easier is if we could use, in a +formal system, the same kind of language I used in describing (in English) +the inference rules earlier: "for all other <EM>z</EM> in the same category as +<EM>y</EM>..." There are two parts to such a formal notation. First, in addition +to the <EM>propositional</EM> variables like <EM>p</EM> used in propositional logic, +we need variables like <EM>x</EM> and <EM>y</EM> that can represent objects in the system +we want to describe. Second, we need a notation for "for all." The formal +system including these additions to propositional logic is called <EM> +predicate</EM> logic. The name is like that used in Logo to refer to +operations with <CODE>true</CODE> or <CODE>false</CODE> outputs because +the statements in predicate logic +involve truth-valued functions of objects analogous to the +Logo predicates. For example, the formula we've been representing +informally as "<EM>x</EM> is <EM>y</EM>" is represented formally using the +predicate function is(<EM>x</EM>,<EM>y</EM>). This +is much like the Logo expression + +<P><PRE>equalp :x :y +</PRE> + +<P>A predicate function of two arguments ("inputs" in Logo) is also +called a <EM>relation</EM> in mathematics. Algebraic relations include ones +like = (equal) and < (less than). + +<P>We are almost ready to show how the uniqueness rule can be expressed as a +formula in predicate logic. If you're not accustomed to mathematical +formalism, this formula is a little scary--perhaps the +scariest thing in this book. But I want you to see it so that +you'll appreciate the fact that just <EM>one</EM> formula of predicate logic +can sum up a rule that would require <EM>many</EM> formulas in propositional +logic. I'm going to introduce a new relation called +"isa" that's true if its first argument is a member of its second +argument. The first must be an individual and the second a category. For +example, isa(pilot,job) is true. And the symbol +∀ means "for all." The uniqueness rule says that if <EM>x</EM> is <EM>y</EM> +then <EM>x</EM> can't also be <EM>z</EM> for any <EM>z</EM> in the same category as <EM>y</EM>. Here's +how to say that formally: + + +<P><CENTER>is(<EM>x</EM>,<EM>y</EM>) → ∀<EM>z</EM> +<STRONG>(</STRONG>(isa(<EM>y</EM>,<EM>a</EM>) ∧ isa(<EM>z</EM>,<EM>a</EM>) +∧ ¬(<EM>y</EM>=<EM>z</EM>)<STRONG>)</STRONG></CENTER><P> + +<P>To indicate the linking of two propositions in the general inference system, +no special rules of inference are required. To say "the reporter wrote +down these two statements; one is true and the other false" is just to say +<EM>p</EM>⊗<EM>q</EM>; I'm using the symbol ⊗ to +represent the <EM>exclusive or</EM> function. This formula is equivalent to +<P><CENTER>(<EM>p</EM>∨<EM>q</EM>) ∧ ¬(<EM>p</EM>∧<EM>q</EM>)</CENTER><P> +A general inference system will know that if it's been told <EM>p</EM>⊗<EM>q</EM> +and then later it learns, say, <EM>p</EM> then it can infer ¬<EM>q</EM>. + +<P>The cub reporter problem is simpler than some of its type in that +the only relevant relation among individuals is "is," which is an + +<EM>equivalence</EM> relation. This means that if Jane is Irving then also +Irving is Jane (the technical name for a relation with that property is +<EM>symmetric</EM>), and also that if Jane is Irving, and Irving is the pilot, +then Jane is the pilot (so the relation is <EM>transitive</EM>). It's +relatively easy to work out all the implications of a proposition about +equivalence relations. + +<P> +By contrast, the Foote problem contains <EM>ordering</EM> relations like "is +later than" that are transitive but not symmetric. To handle such problems +the inference system must have a way to represent "<EM>x</EM> is the last." +Other problems contain relations like "lives in the house next to" that +are symmetric but not transitive. A statement like "Mr. Smith lives in the +house at the end" has to be represented formally as something like "there +is only one person <EM>x</EM> such that <EM>x</EM> lives in the house next to Mr. Smith." + +<P>One reason a general inference system is harder to program than the +special-purpose one I've written in this chapter is that my system makes all +possible inferences from any newly verified or falsified proposition. This +is possible only because there is a finite, fairly small number of such +inferences. Once you introduce variables and predicates, the number of +possible inferences is potentially infinite. A general inference system must +take care not to infer infinitely many useless results. One solution is to +defer the making of inferences until the user of the system asks a question, +and then infer only what's needed to answer that particular question. But +it isn't always easy to know exactly what's needed. + +<P>An inference system like the one I'm vaguely describing is a central part of +the programming language Prolog. In that language, you program not by +issuing instructions that tell the computer what to do, but rather by making +<EM>assertions</EM> that some proposition is true. You can then ask questions +like "for what values of <EM>x</EM> is this formula true?" + +<P> +<H2>Logic and Computer Hardware</H2> + + +<P>Besides inference systems, another area in which logic is important in +computer science is in the design of the computers themselves. In a +computer, information is represented as electrical signals flowing through +wires. (These days, a "wire" is likely to be a microscopic conducting +region on a silicon chip rather than a visible strand of metal, but the +principle is the same.) In almost all computers, each wire may be carrying +one of two voltage levels at any moment. (It is the restriction to two +possible voltages that makes them <EM>binary</EM> computers. It would be + +possible to build <EM>ternary</EM> computer circuits using three +voltages, but I know of no practical application of that idea.) A computer +is built out of small circuit elements called <EM>gates</EM> that combine or +rearrange binary signals in various ways. Perhaps the simplest example of a +gate is an <EM>inverter</EM>; it has one input signal and provides one output +signal that is the opposite of the input. That is, if you have a high +voltage coming into the inverter you get a low voltage out, and vice versa. + +<P>The voltages inside the computer can be thought of as representing numbers +(zeros and ones) or truth values (false and true). From now on I'll use the +symbols 0 and 1 to represent the voltages, but you can mentally replace 0 +with <CODE>false</CODE> and 1 with <CODE>true</CODE> to see how what I'm saying here ties +in with what's gone before. + +<P>Suppose you have a gate with two input wires and one output. What are the +possibilities for how that output is determined by the inputs? Each of the +two inputs can have two possible values; that means that a gate has four +different possible input configurations. For each of those four, the gate +can output 0 or 1. As you can see from the chart below, this means that +there are 16 possible kinds of two-input gates: + +<P><CENTER><TABLE> +<TR><TH align="left">input <EM>p</EM>:<TH> 0 +<TH> 0<TH> 1<TH> 1 +<TR><TH align="left">input <EM>q</EM>:<TH> 0 +<TH> 1<TH> 0<TH> 1 +<TR><TD> +<TR><TH align="left">outputs:<TD> 0 +<TD> 0<TD> 0<TD> 0 +<TR><TH><TD> 0<TD> 0<TD> 0<TD> 1<TD> and (<EM>p</EM>∧<EM>q</EM>) +<TR><TH><TD> 0<TD> 0<TD> 1<TD> 0 +<TR><TH><TD> 0<TD> 0<TD> 1<TD> 1 +<TR><TH><TD> 0<TD> 1<TD> 0<TD> 0 +<TR><TH><TD> 0<TD> 1<TD> 0<TD> 1 +<TR><TH><TD> 0<TD> 1<TD> 1<TD> 0<TD> exclusive or (<EM>p</EM>⊗<EM>q</EM>) +<TR><TH><TD> 0<TD> 1<TD> 1<TD> 1<TD> or (<EM>p</EM>∨<EM>q</EM>) +<TR><TH><TD> 1<TD> 0<TD> 0<TD> 0<TD> nor (not-or, ¬(<EM>p</EM>∨<EM>q</EM>)) +<TR><TH><TD> 1<TD> 0<TD> 0<TD> 1<TD> equivalence (<EM>p</EM>↔<EM>q</EM>) +<TR><TH><TD> 1<TD> 0<TD> 1<TD> 0 +<TR><TH><TD> 1<TD> 0<TD> 1<TD> 1 +<TR><TH><TD> 1<TD> 1<TD> 0<TD> 0 +<TR><TH><TD> 1<TD> 1<TD> 0<TD> 1<TD> implies (<EM>p</EM>→<EM>q</EM>) +<TR><TH><TD> 1<TD> 1<TD> 1<TD> 0<TD> nand (not-and, ¬(<EM>p</EM>∧<EM>q</EM>)) +<TR><TH><TD> 1<TD> 1<TD> 1<TD> 1 +</TABLE></CENTER> + +<P>The table indicates, for example, that a gate whose output is 1 +only when both inputs are 1 is an <EM>and</EM> gate, implementing the usual +logical and operation. The 16 possibilities include all the standard logic +functions as well as several less obviously useful ones. Two gate types +called <EM>nand</EM> and <EM>nor</EM> represent functions rarely used in +mathematical logic but common in computer design because it is sometimes +helpful to have the opposite of the signal you're logically interested in. + +<P>Numbers other than 0 and 1 can't be represented as a single signal in a +single wire. That's why there isn't a "plus gate" along with the and +gates, or gates, and so on; if both inputs to a plus gate were 1, the output +would have to be 2. To add two zero-or-one numbers we need a more +complicated device with <EM>two</EM> output wires, one of which is the +"carry" to the next binary digit: + +<P><CENTER><TABLE> +<TR><TH align="left"><EM>A</EM> input:<TH> 0 +<TH> 0<TH> 1<TH> 1 +<TR><TH align="left"><EM>B</EM> input:<TH> 0 +<TH> 1<TH> 0<TH> 1 +<TR><TD> +<TR><TH align="left">sum out:<TD> 0 +<TD> 1<TD> 1<TD> 0 +<TR><TH align="left">carry out:<TD> 0 +<TD> 0<TD> 0<TD> 1 +</TABLE></CENTER> + +<P>These sum and carry outputs can be defined in terms of logical +operations: + +<P> +<P><CENTER><TABLE><TR><TD align="right">Sum<TD> = +<TD> <EM>A</EM>⊗<EM>B</EM> +<TR><TD align="right">Carry<TD> = +<TD> <EM>A</EM>∧<EM>B</EM> +</TABLE></CENTER><P> + + +<P>Exclusive or gates are, in fact, not generally used as basic +hardware components, so this device is traditionally represented in terms of +and gates, or gates, and inverters: + +<P><CENTER><IMG SRC="half-adder.gif" ALT="figure: half-adder"></CENTER> + +<P>The device we've just built is called a <EM>half-adder</EM> for +reasons that should become clear in a moment. + +<P>To represent numbers larger than 1 we have to use more than one signal wire. +Each signal represents a binary digit, or <EM>bit,</EM> that is implicitly +multiplied by a power of 2 just as in the ordinary decimal representation of +numbers each digit is implicitly multiplied by a power of 10. For example, +if we have three signal wires for a number, they have multipliers of 1, 2, +and 4; with these signals we can represent the eight numbers from 0 (all +signals 0) to 7 (all signals 1). When we want to add two such three-bit +numbers, the sum for all but the rightmost bit can involve a carry <EM> +in</EM> as well as a carry out. The circuit for each bit position must have +<EM>three</EM> inputs, including one for the carry from the next bit over as +well as the two external inputs. The outputs are found using these formulas: + +<P> +<P><CENTER><TABLE><TR><TD align="right">Sum<TD> = +<TD> (<EM>A</EM>⊗<EM>B</EM>)⊗CarryIn +<TR><TD align="right">CarryOut<TD> = +<TD> (<EM>A</EM>∧<EM>B</EM>)∨ +<STRONG>(</STRONG>(<EM>A</EM>⊗<EM>B</EM>)∧CarryIn<STRONG>)</STRONG> +</TABLE></CENTER><P> + +<P>This circuit can be built using two half-adders: + +<P><CENTER><IMG SRC="full-adder.gif" ALT="figure: full-adder"></CENTER> + +<P>To add two three-bit numbers we connect three adders together this +way: + +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/three-adders.gif" ALT="figure: three-adders"></CENTER> + +<P>The carry out signal from the leftmost adder (the one representing + +the largest power of 2) is the <EM>overflow</EM> signal; if it's true, the +sum didn't fit in the number of bits provided. Many computers use this +signal to <EM>interrupt</EM> the execution of their programs so that people +don't end up seeing incorrect results. + +<P>The phrase "computer logic" is widely used, even by non-experts, to refer +to the inner workings of a computer. Many people, though, think that the +phrase describes the <EM>personality</EM> of the computer, which they imagine + +to be like that of Mr. Spock. "Computers may be able to play chess, but +they can't write poetry, because that isn't logical." Here you've seen the +real meaning of the phrase: Just as a Logo program has procedures defined in +terms of subprocedures and ultimately in terms of primitive procedures, the +capabilities of a computer itself are built out of smaller pieces, and the +primitive hardware components compute logical, rather than arithmetic, +functions. (For a computer to exhibit Mr. Spock's sense of purpose, +understanding of cause and effect, drive for self-preservation, loyalty to +his species and his government, and so on, would be no less miraculous than +for it to write a love poem or throw a temper tantrum. Later we'll discuss +the efforts of artificial intelligence researchers to produce such miracles.) + +<P><H2>Combinatorics</H2> + + +<P>Earlier I listed the 16 possible logical functions of two logical arguments. +I could have figured out that there are 16 without actually listing them +this way: If a function has two arguments, and each argument has two +possible values, that makes 2<SUP><SMALL>2</SMALL></SUP> possible combinations of argument values. +A logical function is determined by its result for each of those four +possible argument combinations. (The four are <EM>f</EM>(0,0), <EM>f</EM>(0,1), <EM>f</EM>(1,0), +and <EM>f</EM>(1,1).) There are two possible results for <EM>f</EM>(0,0), two for +<EM>f</EM>(0,1), and so on; the number of possible functions is the product of all +these twos, 2<SUP><SMALL>2<SUP><SMALL>2</SMALL></SUP></SMALL></SUP> or 16. + +<P>The mathematics of counting how things can be combined is called +<EM>combinatorics.</EM> The problem we've just done illustrates a fundamental +rule of combinatorics, namely that the number of possibilities for a choice +with several components is the product of the number of possibilities for +each component choice. This may be easier to understand with an example in +which not all the relevant numbers are 2. Here's a classic: Suppose you +have a group of four men and three women, and you want to form a committee +of one man and one woman chosen from this group. How many such committees +are possible? There are 4 choices for the male member of the committee and +3 choices for the female member; that means 4×3 or 12 committees. + +<P>(The multiplication rule only works if the component choices are <EM> +independent</EM>; that is, the possible outcomes of one choice can't be +affected by the outcome of any of the others. For example, if our +committees are to have a chairperson who can be of either sex and then two +other members, one man and one woman, you can't say "there are 7 choices +for the chairperson, times 4 for the man, times 3 for the woman" because +after choosing the chairperson the number of choices for the other members +is changed depending on the sex of the chair. There are two correct ways +to solve this problem. One is to say "The chairperson is either male or +female. If male, there are 4 possible chairs, times 3 possible other male +members, times 3 possible female members, for 36 possible committees. If +female, there are 3 possible chairs, times 4 possible male members, times 2 +possible other female members, for 24 committees. The total is 36+24 or +60 committees." The second solution is to pick the chairperson <EM>last</EM>; +then you say "There are 4 possible male members, times 3 possible females, +times 5 possible chairs (7 people in the original group minus 2 already +chosen)." Apart from arithmetic errors, almost all the mistakes people make +in solving combinatorics problems come from forgetting that events have to +be independent to allow you to multiply the choices.) + +<P>Let's return to logical functions for a moment. Suppose we experiment with +a ternary logic in which the possible values are yes, no, and maybe. (You +can represent these using the numbers 0, 1, and 2.) How many three-argument +ternary logic functions are there? Is it 3<SUP><SMALL>(3<SUP><SMALL>3</SMALL></SUP>)</SMALL></SUP> or is it (3<SUP><SMALL>3</SMALL></SUP>)<SUP><SMALL>3</SMALL></SUP>? +(It doesn't matter which way you group the twos for the binary logic version +because the two groupings have the same value, 16, but this isn't true with +threes.) How many two-argument ternary logic functions are there? +2<SUP><SMALL>(3<SUP><SMALL>2</SMALL></SUP>)</SMALL></SUP>? 3<SUP><SMALL>(2<SUP><SMALL>3</SMALL></SUP>)</SMALL></SUP>? (3<SUP><SMALL>3</SMALL></SUP>)<SUP><SMALL>2</SMALL></SUP>? How many three-argument binary logic +functions? The virtue of these problems is that you can check your own +answers by listing all the possible functions as I did for the two-argument +binary logic functions. + +<P>Most people are introduced to combinatorics +by way of <EM>probability,</EM> +the mathematics of gambling. Given a number of equally likely possible +situations, some of which win a bet and the rest of which lose it, the +probability of winning is a ratio: + +<P><CENTER><IMG SRC="probability.gif"></CENTER><P> +The role of combinatorics is to help in computing the numerator and +denominator of that fraction. + +<P> + +For example, suppose you have six brown socks and four blue socks in a +drawer, and you pull out two socks without looking. What is the probability +of getting a matching pair? I'm going to give each sock a name like +<EM>brown</EM><SUB><SMALL>3</SMALL></SUB> for the third brown sock so that we can talk about individual socks +even if they're the same color. How many possible pairs of socks are there? +That is, given the set +<P><CENTER>{<EM>brown</EM><SUB><SMALL>1</SMALL></SUB>, +<EM>brown</EM><SUB><SMALL>2</SMALL></SUB>, ..., +<EM>brown</EM><SUB><SMALL>6</SMALL></SUB>, +<EM>blue</EM><SUB><SMALL>1</SMALL></SUB>, ... +<EM>blue</EM><SUB><SMALL>4</SMALL></SUB>}</CENTER><P> +containing ten socks, how many two-sock subsets are there? + +<P>The first step in answering this question is to notice that we have 10 +choices for the first sock and then 9 choices for the second. So there are +10×9 ways to make the two choices. (There is a subtle point here +that some textbooks don't bother explaining. The choice of the second sock +is <EM>not</EM> independent of the first choice, since we can't choose the +same sock twice. However, the <EM>number</EM> of second choices is always 9, +even though the particular nine available socks depend on the first choice. +So we can get away with multiplying in this example.) + +<P>This isn't quite the answer we want, though. We've shown that there are 90 +<EM>ordered pairs</EM> of socks. But once we get the socks out of the +drawer, it doesn't matter which we picked first. In other words, if we say +there are 90 possible choices, we are counting +{<EM>brown</EM><SUB><SMALL>2</SMALL></SUB>, <EM>brown</EM><SUB><SMALL>5</SMALL></SUB>} and {<EM>brown</EM><SUB><SMALL>5</SMALL></SUB>, <EM>brown</EM><SUB><SMALL>2</SMALL></SUB>} +as two different choices. Since we don't care which sock came out of the +drawer first, we are really counting every pair twice, so there are only +90/2 or 45 possible pairs. + +<P>An ordered subset of a set is called a <EM>permutation;</EM> +a subset without +a particular order is a <EM>combination.</EM> We say that there are 90 +permutations of ten things taken two at a time; there are 45 combinations of +ten things taken two at a time. + +<P>It turns out that combinations are what matters most of the time; it's +relatively rare for permutations to turn up in a math problem. An exception +is the device wrongly called a "combination lock"; to open one, you must +know a particular permutation of the possible numbers. My high school +locker "combination" was 18-24-14. If I tried the same numbers in a +different order, like 24-18-14, the lock wouldn't open. (Actually it's +misleading for me to use this example because the same number can appear +twice in most locks of this type, so the "combination" is not a subset of +the available numbers. If there are 50 numbers available, the total number +of possibilities is not 50×49×48 but rather 50×50×50. These lock-opening patterns are therefore neither permutations nor +combinations but something else that we might call "permutations with +repetition allowed.") + +<P>We haven't finished solving the sock problem. How many of the possible +pairs of socks are matching pairs? One way to find out would be to list all +the possible pairs and actually count how many of them match. This is the +sort of thing computers do well. First we have to write a procedure that +takes as input a list and a number, and outputs a list of lists, each of +which is a subset of the input list whose length is the input number. That +is, we want to take + +<P><PRE>combs [brown1 brown2 ... brown6 blue1 ... blue4] 2 +</PRE> + +<P>and this should output a list of pairs: + +<P><PRE>[[brown1 brown2] [brown1 brown3] ... [brown4 blue3] ... [blue3 blue4]] +</PRE> + +<P>This is a fairly tricky program to write. Try it before you read +further. Can you reduce the problem to a smaller, similar problem? Don't +forget that we want combinations, not permutations, so the output can't have +two sublists containing the same elements. + +<P>To make sure that each combination appears in the result in only one order, +we can decide explicitly what that order will be. The most convenient thing +is to say that the elements will appear in each sublist in the same order in +which they appear in the original list. That is, since the input list has +<CODE>brown2</CODE> before <CODE>blue3</CODE>, the output will contain the list + +<P><PRE>[brown2 blue3] +</PRE> + +<P>but not the list + +<P><PRE>[blue3 brown2] +</PRE> + +<P>It follows that the very first element of the input list, <CODE> +brown1</CODE>, can only appear as the first element of any output sublist. In +other words, there are two kinds of sublists: ones with <CODE>brown1</CODE> as +their first element and ones that don't include <CODE>brown1</CODE> at all. This +is a way to divide the problem into smaller pieces. + +<P>If we are looking for <EM>n</EM>-element subsets, the first kind consists of <CODE> +brown1</CODE> stuck in front of a smaller subset of <EM>n</EM>−1 elements chosen from the +remainder (the <CODE>butfirst</CODE>) of the input list. The second kind of subset +is an <EM>n</EM>-element subset of the <CODE>butfirst</CODE>. We can collect all of each +kind by a recursive invocation of the procedure we're going to write, then +append the two collections and output the result. So the procedure will +look like this: + +<P><PRE>to combs :list :howmany +... <stop rule> ... +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end +</PRE> + +<P>By now you've had a lot of experience writing +recursive procedures, +but I'm going over this one in detail for two reasons: It's tricky and it's a +model for solving many other combinatorial problems. What makes it tricky +is a combination of two things. One is that it's recursive twice; that is, +there are two recursive invocations of <CODE>combs</CODE> within <CODE>combs</CODE>. This +makes the control structure very different from the + +<P><PRE>to blah :list +output fput (<CODE><EM>something</EM></CODE> first :list) (blah butfirst :list) +end +</PRE> + +<P>sort of recursion that may be more familiar. The second tricky +part is that there are two input variables, each of which may be made smaller +(by <CODE>butfirst</CODE>ing or by subtracting 1) but need not be in a particular +recursive call. + +<P>One implication of these complicating factors is that we need <EM>two</EM> +stop rules. It may be obvious that we need one for the situation of +counting <CODE>:howmany</CODE> down to zero, but we also need one for <CODE>:list</CODE> +getting too small. Ordinarily this latter would be an <CODE>emptyp</CODE> test, but +in fact any list whose length is less than <CODE>:howmany</CODE> is too small, not +just the empty list. Here is the finished procedure: + +<P><PRE>to combs :list :howmany +if equalp :howmany 0 [output [[]]] +if equalp :howmany count :list [output (list :list)] +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end + +? <U>show combs [a b c d e] 3</U> +[[a b c] [a b d] [a b e] [a c d] [a c e] [a d e] + [b c d] [b c e] [b d e] [c d e]] +</PRE> + +<P>Now we can use <CODE>combs</CODE> on the sock problem. (Note: The procedure <CODE> +socks</CODE> shown here is not the one in the program file; there will be a +modified version a few paragraphs down the road.) + +<P><PRE>to socks :list +localmake "total combs :list 2 +localmake "matching filter [equalp butlast first ? butlast last ?] ~ + :total +print (sentence [There are] count :total [possible pairs of socks.]) +print (sentence [Of these,] count :matching [are matching pairs.]) +print sentence [Probability of match =] ~ + word (100*(count :matching)/(count :total)) "% +end + +? <U>socks [brown1 brown2 brown3 brown4 brown5 brown6</U> + <U>blue1 blue2 blue3 blue4]</U> +There are 45 possible pairs of socks. +Of these, 21 are matching pairs. +Probability of match = 46.6666667% +</PRE> + +<P>The answer is that the probability of a matching pair is just +under half. The template used in the invocation of <CODE>filter</CODE> in <CODE> +socks</CODE> depends on the fact that two socks match if their names are equal +except for the last character, such as <CODE>brown3</CODE> and <CODE>brown4</CODE>. + +<P>I've numbered the socks because it's easier for us to talk about how the +program works (and about how the underlying mathematics works, too) if we +can identify an individual sock. But it's worth noting that the program +doesn't really need individual sock names. We could instead use the list + +<P><PRE>[brown brown brown brown brown brown blue blue blue blue] +</PRE> + +<P>and change the <CODE>filter</CODE> template to + +<P><PRE>[equalp first ? last ?] +</PRE> + +<P>The program will generate some <CODE>[brown brown]</CODE> pairs, some +<CODE>[brown blue]</CODE> pairs, and some <CODE>[blue blue]</CODE> pairs. The number of +pairs will still be 45 and the number of matching pairs will still be 21. + +<P>Having come to that realization, we can make the "user interface" a little +smoother by having <CODE>socks</CODE> accept an input list like + +<P><PRE>[6 brown 4 blue] +</PRE> + +<P>and expand that into the desired list of ten socks itself. Here is +the final program: + +<P><PRE>to socks :list +localmake "total combs (expand :list) 2 +localmake "matching filter [equalp first ? last ?] :total +print (sentence [There are] count :total [possible pairs of socks.]) +print (sentence [Of these,] count :matching [are matching pairs.]) +print sentence [Probability of match =] ~ + word (100*(count :matching)/(count :total)) "% +end + +to expand :list +if emptyp :list [output []] +if numberp first :list ~ + [output cascade (first :list) + [fput first butfirst :list ?] + (expand butfirst butfirst :list)] +output fput first :list expand butfirst :list +end + +? <U>socks [6 brown 4 blue]</U> +There are 45 possible pairs of socks. +Of these, 21 are matching pairs. +Probability of match = 46.6666667% +</PRE> + +<P>My reason for presenting this refinement of the program is that it offers a +concrete opportunity for reflection on how you can tell which differences are +important in a combinatorics problem. In discussing the first version of +the program, I said that the two lists + +<P><PRE>[brown2 brown5] and [brown5 brown2] +</PRE> + +<P>represent the same pair of socks, so both shouldn't be included in +the list of lists output by <CODE>combs</CODE>. Now I'm saying that several lists +that look identical like + +<P><PRE>[brown brown] +</PRE> + +<P>represent <EM>different</EM> pairs of socks and must all be counted. +It would be a mistake to say, "There are three possibilities: brown-brown, +brown-blue, and blue-blue. So the probability of a match is 2/3." It's +true that there are three <EM>kinds</EM> of pairs of socks, but the three +kinds are not equally represented in the list of 45 possible pairs. + +<P><H2>Inductive and Closed-Form Definition</H2> + +<P>The usual approach to problems like the one about the socks is not to +enumerate the actual combinations, but rather to compute the <EM>number</EM> +of combinations directly. There are formulas for both number of +combinations and number of permutations. Usually the latter is derived +first because it's easier to understand. + +<P>With 10 socks in the drawer, the number of two-sock permutations is +10×9. If we'd wanted three socks for a visiting extraterrestrial +friend, the number of permutations would be 10×9×8. In +general, if we have <EM>n</EM> things and we want to select <EM>r</EM> of them, the number +of permutations is +<P><CENTER><IMG SRC="math11.gif" ALT="math display"></CENTER><P> +Mathematicians don't like messy formulas full of dots, so this is usually +abbreviated using the factorial function. The notation "<EM>n</EM>!" is +pronounced "<EM>n</EM> factorial" and represents the product of all the integers +from 1 to <EM>n</EM>. Using this notation we can write +<P><CENTER><IMG SRC="math12.gif" ALT="math display"></CENTER><P> +This is an elegant formula, but you should resist the temptation to use it +as the basis for a computer program. If you write + +<P><PRE>to perms :n :r +output (fact :n)/(fact (:n-:r)) +end + +to fact :n +output cascade :n [# * ?] 1 +end +</PRE> + +<P>then you're doing more multiplications than necessary, plus an +unnecessary division. Instead, go back to the earlier version in which <EM>r</EM> +terms are multiplied: + +<P><PRE>to perms :n :r +if :r=0 [output 1] +output :n * perms :n-1 :r-1 +end +</PRE> + +<P>The set of all permutations of <EM>n</EM> things taken <EM>r</EM> at a time includes +several rearrangements of each <EM>combination</EM> of <EM>n</EM> things <EM>r</EM> at a +time. How many rearrangements of each? Each combination is a set of <EM>r</EM> +things, so the number of possible orderings of those <EM>r</EM> things is the +number of permutations of <EM>r</EM> things <EM>r</EM> at a time, <EM><SUB><SMALL>r</SMALL></SUB>P<SUB><SMALL>r</SMALL></SUB></EM> or <EM>r</EM>!. +<EM><SUB><SMALL>n</SMALL></SUB>P<SUB><SMALL>r</SMALL></SUB></EM> is greater than <EM><SUB><SMALL>n</SMALL></SUB>C<SUB><SMALL>r</SMALL></SUB></EM>, the number of combinations of <EM>n</EM> +things taken <EM>r</EM> at a time, by this factor. In other words, if each +combination corresponds to <EM>r</EM>! permutations, then the number of +permutations is <EM>r</EM>! times the number of combinations. So we have +<P><CENTER><IMG SRC="math13.gif" ALT="math display"></CENTER><P> +The notation <IMG SRC="nchooser.gif"> is much more commonly used in mathematics and +computer science texts than <EM><SUB><SMALL>n</SMALL></SUB>C<SUB><SMALL>r</SMALL></SUB></EM>. It's pronounced "<EM>n</EM> choose <EM>r</EM>." + +<P>The traditional way to do the sock problem is this: The total number of +possible pairs of socks is <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/10choose2.gif">. The number of matching pairs is +equal to the number of brown pairs plus the number of blue pairs. The +number of brown pairs is the number of combinations of 6 brown socks chosen +2 at a time, or <IMG SRC="6choose2.gif">. Similarly, the number of pairs of blue socks +is <IMG SRC="4choose2.gif">. So +<P><CENTER><IMG SRC="math14.gif" ALT="math display"></CENTER><P> +which is the same answer we got by enumerating and testing all the possible +pairs. + +<P>A formula like +<P><CENTER><IMG SRC="math15.gif" ALT="math display"></CENTER><P> +defines a mathematical function in terms of other, more elementary functions. +It is comparable to a Logo procedure defined in terms of primitives, like + +<P><PRE>to second :thing +output first butfirst :thing +end +</PRE> + +<P>The "primitives" of mathematics are addition, subtraction, and +so on, along with a few more advanced ones like the trigonometric and +exponential functions. These are called "elementary functions" and a +formula that defines some new function in terms of those is called a +<EM>closed form definition.</EM> + +<P> + +<P>The function <IMG SRC="nchooser.gif"> could also be defined in a different way based on +the ideas in the <CODE>combs</CODE> program we used to enumerate combinations. The +combinations fall into two categories, those that include the first element +and those that don't. So the number of combinations is the sum of the +numbers in each category: +<P><CENTER><IMG SRC="math16.gif" ALT="math display"></CENTER><P> +This is called an <EM>inductive definition.</EM> It is analogous to a +recursive procedure in Logo. + +<P> + +<P>These two formulas provide alternative definitions for the <EM>same</EM> +function, just as two Logo procedures can employ different algorithms but +have the same input-output behavior. How do we know that the two +definitions of <IMG SRC="nchooser.gif"> really do define the same function? Each +definition was derived from the fundamental definition of "the number of +combinations of <EM>n</EM> things taken <EM>r</EM> at a time" by different arguments. +If those arguments are correct, the two versions must define the same +function because there is just one correct number of combinations. It is +also possible to prove the two definitions equivalent by algebraic +manipulation; start with the closed form definition and see if it does, in +fact, obey the requirements of the inductive definition. For example, if +<EM>r</EM>=0 we have +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/math17.gif" ALT="math display"></CENTER><P> +(It may not be obvious that 0! should be equal to 1, but mathematicians +define the factorial function that way so that the formula <EM>n</EM>! = <EM>n</EM>·(<EM>n</EM>−1)! +remains true when <EM>n</EM>=1.) See if you can verify the other two parts of the +inductive definition. Here's a hint: +<P><CENTER><IMG SRC="math18.gif" ALT="math display"></CENTER><P> + +<P>Why would anyone be interested in an inductive definition when the closed +form definition is mathematically simpler and also generally faster to +compute? There are two reasons. First, some functions don't have closed +form definitions in terms of elementary functions. For those functions, +there is no choice but to use an inductive definition. Second, sometimes +when you start with a non-formal definition of a function in terms of its +purpose, like "the number of combinations..." for <IMG SRC="nchooser.gif">, it may be +easier to see how to translate that into an inductive definition as a first +step, even if it later turns out that there is also a less obvious closed +form. In fact, that's what I did in presenting the idea of combinations. I +found it more straightforward to understand the inductive definition because +it made sense to think about the actual combinations and not merely how many +of them there are. (In fact there is a mathematical technique called <EM> +generating functions</EM> that can sometimes be used to transform an +inductive definition into a closed form definition, but that technique +requires calculus and is beyond the scope of this book.) + +<P><H2>Pascal's Triangle</H2> + +<P>In addition to closed form and inductive definitions, it's often helpful to +present a sort of partial definition of a function in the form of a +table of values. (For +logic functions, with only a finite number of possible values +for the arguments of the function, such a table is actually a complete +definition.) Partial definitions in a table of values can be particularly +useful when the function displays some regularity that allows values outside +the table to be computed easily based on the values in the table. For +example, the sine function is <EM>periodic</EM>; its values repeat in cycles +of 360 degrees. If you need to know the sine of 380 degrees, you can look +up the sine of 20 degrees and that's the answer. For functions of two +variables, like addition and multiplication, these function tables are often +presented as square arrays of numbers. In elementary school you learned the +addition and multiplication tables for numbers up to 10, along with +algorithms for reducing the addition and multiplication of larger numbers to +a sequence of operations on single digits. + +<P>The function <IMG SRC="nchooser.gif"> is a function of two variables, so it would +ordinarily be presented as a square table like the multiplication table, +except for the fact that this particular function is meaningfully defined +only when <EM>r</EM>≤<EM>n</EM>. (There are no combinations of three things taken five +at a time, for example, so <IMG SRC="3choose5.gif"> is 0.) So instead of a square +format like this: +<P><CENTER><TABLE> +<TR><TH><SUB><SMALL><EM>r</EM></SMALL></SUB>\<SUP><SMALL><EM>n</EM></SMALL></SUP> +<TH> 0<TH> 1<TH> 2<TH> 3<TH> 4<TH> 5 +<TR><TH>0<TD align="center"> 1<TD align="center"> 1<TD align="center"> 1 +<TD align="center"> 1<TD align="center"> 1<TD align="center"> 1 +<TR><TH>1<TD align="center"> 0<TD align="center"> 1<TD align="center"> 2 +<TD align="center"> 3<TD align="center"> 4<TD align="center"> 5 +<TR><TH>2<TD align="center"> 0<TD align="center"> 0<TD align="center"> 1 +<TD align="center"> 3<TD align="center"> 6<TD align="center"> 10 +<TR><TH>3<TD align="center"> 0<TD align="center"> 0<TD align="center"> 0 +<TD align="center"> 1<TD align="center"> 4<TD align="center"> 10 +<TR><TH>4<TD align="center"> 0<TD align="center"> 0<TD align="center"> 0 +<TD align="center"> 0<TD align="center"> 1<TD align="center"> 5 +<TR><TH>5<TD align="center"> 0<TD align="center"> 0<TD align="center"> 0 +<TD align="center"> 0<TD align="center"> 0<TD align="center"> 1 +</TABLE></CENTER><P> +this function is traditionally presented in a triangular form called +"Pascal's Triangle" after Blaise Pascal (1623-1662), who invented the +mathematical theory of probability along with Pierre de Fermat (1601-1665). +Pascal didn't invent the triangle, but he did pioneer its use in +combinatorics. Each row of the triangle contains the nonzero values of +<IMG SRC="nchooser.gif"> for a particular <EM>n</EM>: +<P><CENTER><TABLE> +<TR><TD align="center">1 +<TR><TD align="center">1 1 +<TR><TD align="center">1 2 1 +<TR><TD align="center">1 3 3 1 +<TR><TD align="center">1 4 6 4 1 +<TR><TD align="center">1 5 10 10 5 1 +</TABLE></CENTER><P> +Pascal's Triangle is often introduced in algebra because the numbers in row +<EM>n</EM> (counting from zero) are the <EM>binomial coefficients,</EM> the constant +factors in the terms in the expansion of (<EM>a</EM>+<EM>b</EM>)<SUP><SMALL><EM>n</EM></SMALL></SUP>. For example, +<P><CENTER><IMG SRC="math21.gif" ALT="math display"></CENTER><P> + +<P>Do you see why the binomial coefficients are related to combinations? An +expression like (<EM>a</EM>+<EM>b</EM>)<SUP><SMALL>4</SMALL></SUP> is a sum of products of four <EM>A</EM>s and <EM>B</EM>s. (How +many such products? Each term involves four choices between <EM>A</EM> and <EM>B</EM>; +there are 2 ways to make each choice, and the choices are independent, so +there are 2<SUP><SMALL>4</SMALL></SUP> possible products.) These products are combined into terms +based on the fact that some are equal to each other, such as <EM>aaab</EM> and +<EM>abaa</EM>, both of which contribute to the <EM>a</EM><SUP><SMALL>3</SMALL></SUP><EM>b</EM> term. How many arrangements +of three <EM>A</EM>s and one <EM>B</EM> are there? That's like asking how many ways there +are to choose one slot for a <EM>B</EM> out of four possible slots, which is +<IMG SRC="4choose1.gif">. + +<P>Can you predict what the coefficients will be in the expansion of +(<EM>a</EM>+<EM>b</EM>+<EM>c</EM>)<SUP><SMALL>4</SMALL></SUP>? For example, what is the coefficient of <EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM>? Try +to multiply it out and see if your formula is right. + +<P>Everyone is taught in school that each number in Pascal's Triangle, except +for the 1s at the ends, is the sum of the two numbers above it. But this is +usually presented as a piece of magic with no explanation. It's not obvious +how that fact is connected to the formula expressing <IMG SRC="nchooser.gif"> in terms +of factorials. But the technique I used in writing the <CODE>combs</CODE> procedure +to enumerate the actual combinations explains how Pascal's Triangle works. +The set of all combinations of <EM>n</EM> things taken <EM>r</EM> at a time can be divided +into those combinations that include the first of the <EM>n</EM> things and those +that don't. How many of the former are there? Each such combination must +be completed by adjoining to that first thing <EM>r</EM>−1 out of the remaining +<EM>n</EM>−1 available things, so there are <IMG SRC="n-1chooser-1.gif"> such combinations. +The second category, those not containing the first thing in the list, +requires us to choose <EM>r</EM> things out of the remaining <EM>n</EM>−1, so there are +<IMG SRC="n-1chooser.gif"> of them. So <IMG SRC="nchooser.gif"> must be the sum of those two +numbers, which are indeed the ones above it in the triangle. + +<P>Thinking about the triangle may also help you to understand why <CODE>combs</CODE> +needs two stop rules; each row contains <EM>two</EM> numbers, the ones (pun) +at each end, that can't be computed as the sum of two other numbers. + +<P><H2>Simulation</H2> + + +<P>Yet another approach to solving the sock problem would be the +experimental method: Load a drawer with six brown and four blue socks, pull out pairs +of socks a few thousand times, and see how many of the pairs match. The +actual experiment would be time-consuming and rather boring, but we can +<EM>simulate</EM> the experiment with a computer program. The idea is to use +random numbers to represent the random choice of a sock. + +<P><PRE>to socktest +localmake "first ~ + pick [brown brown brown brown brown brown blue blue blue blue] +localmake "second ~ + pick (if equalp :first "brown + [[brown brown brown brown brown blue blue blue blue]] + [[brown brown brown brown brown brown blue blue blue]] ) +output equalp :first :second +end +</PRE> + +<P><CODE>Socktest</CODE> is a predicate that simulates one trial of picking +a pair of socks and outputs <CODE>true</CODE> if the socks match. Notice how the +available choices for the second sock depend on which color sock was chosen +first. (It's a little unaesthetic that this particular selection of six +brown and four blue socks is built into the program, with three slightly +different lists explicitly present inside <CODE>socktest</CODE>. It would be both +more elegant and more flexible if <CODE>socktest</CODE> could take a list like +<CODE>[6 brown 4 blue]</CODE> as input, like <CODE>socks</CODE>, and compute the list of +possibilities for the second sock itself. But right now I'm more interested +in showing how a simulation works than in programming style; you can make +that change yourself if you like.) + +<P>What we want to do is invoke <CODE>socktest</CODE> repeatedly and keep track of how +many times the output is <CODE>true</CODE>. That can be done with an instruction +like + +<P><PRE>print (cascade 1000 [? + if socktest [1] [0]] 0) / 10 +</PRE> + +<P>I divide by 10 so that the result will be expressed as a percent +probability. (If I made 100 trials instead of 1000 the output from <CODE> +cascade</CODE> would already be a percentage.) Your results will depend on the +random number generator of your computer. I tried it three times and got +results of 50.1%, 50.8%, and 45.5%. I then did 10,000 trials at once +with a result of 48.78%. The result expected on theoretical grounds was +46 <SUP><SMALL>2</SMALL></SUP>⁄<SUB><SMALL>3</SMALL></SUB>%. + +<P>Simulation is generally much slower than either of the techniques we used +earlier (enumeration of possibilities and direct computation of the number +of possibilities), and it gives results that are only approximately correct. +So why would anyone want to use this method? For a simple problem like +this, you probably wouldn't. But some combinatorics problems are too +complicated to be captured by a simple formula. For example, what is the +probability of winning a game of solitaire? (To make this a sensible +question, you'd have to decide on a particular set of strategy rules to +determine which card to play next when there are several possibilities. The +rule could be "play the higher ranking card" or "choose a card at +random," for example.) In principle this question could be answered +exactly, since there are only a finite number of ways a deck of cards can be +arranged and we could analyze each of them. But in practice the most +reasonable approach is probably to write a solitaire simulator and have it +play out a few thousand randomly ordered hands. + +<P>Solitaire is a rather complicated game; even a simulator for it would be +quite a large project. A more manageable one, if you'd like something to +program, would be a craps simulator. Remember that the 11 possible results +of rolling two dice (2 to 12) are not equally likely! You have to simulate +each die separately. + +<P><H2>The Simplex Lock Problem</H2> + +<P>This is a picture of a Simplex lock, so called because it's +manufactured by Simplex Security Systems, Inc. It is a five-button mechanical +(i.e., no electricity) combination lock with an unusual set of possible +combinations. As an example of a challenging problem in combinatorics, I'd +like you to figure out how many possible combinations there are. + +<P><CENTER><IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/lock.gif" ALT="figure: lock"></CENTER> + + + +<P>What makes this lock unusual is that a combination can include more than one +button pushed at the same time. For example, one possible combination is +"2, then 1 and 4 at the same time, then 3." Here are the precise rules: + +<P><P> +<TABLE><TR><TH align="right" valign="top">1.<TD> <TD valign="top"> Each button may be used at most once. For example, "2, then 2 and 3 at +the same time" is not allowed. +<TR><TH align="right" valign="top">2.<TD> <TD valign="top"> Each push may include any number of buttons, from one to five. For +example, one legal combination is "hit all five buttons at once with your +fist." (But hitting all five buttons can't be part of a larger combination +because of rule 1.) + +<P></TABLE><P> + +<P>It follows from these rules that there can be at most five +distinct pushes. (Do you see why?) The rules also allow for the null +combination, in which you don't have to push any buttons at all. + +<P>When working on this problem, don't forget that when two or more buttons are +pushed at the same time, their order doesn't matter. That is, you shouldn't +count "2 and 3 together, then 5" and "3 and 2 together, then 5" as two +distinct combinations. (For this reason, the Simplex lock <EM>is</EM> +entitled, at least in part, to the name "combination lock"!) + +<P>Try to figure out how many combinations there are before reading further. +You can enumerate all the possibilities or you can derive a formula for the +number of possibilities. You might want to start with a smaller number of +buttons. (As a slight hint, when you buy one of these locks, the box it +comes in says "thousands of combinations.") + +<P>I first attacked this problem by trying to enumerate all the possible +combinations, but that turns out to be quite messy. The trouble is that it +isn't obvious how to <EM>order</EM> the combinations, so it's hard to be sure +you haven't missed any. Here is how I finally decided to do it. First of +all, divide the possible combinations into six categories depending on how +many buttons (zero to five) they use. There is exactly one combination +using zero buttons, and there are five using one button each. After that it +gets tricky because there are different <EM>patterns</EM> of simultaneous +pushes within each category. For example, for combinations using two +buttons there are two patterns: the one in which they're pressed together +(<CODE>x-x</CODE>) and the one in which they're pressed separately (<CODE>x x</CODE>). +(I'm introducing a notation for patterns in which hyphens connect buttons +that are pressed together and spaces connect the separate pushes.) How many +distinct combinations are there in each of those patterns? Figure it out +before reading on. + +<P>In the <CODE>x x</CODE> pattern there are <SUB><SMALL>5</SMALL></SUB><EM>P</EM><SUB><SMALL>2</SMALL></SUB> "combinations" because the +order in which you push the buttons matters. In the <CODE>x-x</CODE> pattern there +are only <IMG SRC="5choose2.gif"> combinations because the two buttons are pushed +together; <CODE>1-4</CODE> and <CODE>4-1</CODE> are the same combination. Altogether +there are 20+10 or 30 combinations usng two of the five buttons. + +<P>Beyond this point it gets harder to keep track of the different patterns. +Among the three-button patterns are <CODE>x-x x</CODE>, <CODE>x x x</CODE>, and <CODE> +x-x-x</CODE>. How many more are there? How many four-button patterns? You might, +at this point, like to see if you can finish enumerating all the +possibilities for the five-button lock. + +<P>My solution is to notice that in a three-button pattern, for example, there +are two slots between the <CODE>x</CODE>s, and each slot has a space or a hyphen. +If I think of those slots as binary digits, with 0 for space and 1 for +hyphen, then each pattern corresponds to a 2-bit number. There are four +such numbers, 00 to 11 (or 0 to 3 in ordinary decimal notation). + +<P><TABLE><TR><TH>number<TH> <TH>pattern +<TR><TD align="center"> +<PRE> +00 +01 +10 +11 +</PRE><TH> <TD align="center"> +<PRE> +x x x +x x-x +x-x x +x-x-x +</PRE></TABLE> + +<P>Similarly, there are eight four-button patterns: + +<P><TABLE><TR><TH>number<TH> <TH>pattern +<TR><TD align="center"> +<PRE> +000 +001 +010 +011 +100 +101 +110 +111 +</PRE><TH> <TD align="center"> +<PRE> +x x x x +x x x-x +x x-x x +x x-x-x +x-x x x +x-x x-x +x-x-x x +x-x-x-x +</PRE></TABLE> + +<P>And there are 16 five-button patterns, from 0000 to 1111. + +<P>How many combinations are there within each pattern? There are two +different ways to go about calculating that number. To be specific, let's +consider four-button patterns. The way I chose to do the calculation was to +start with the idea that there are <SUB><SMALL>5</SMALL></SUB><EM>P</EM><SUB><SMALL>4</SMALL></SUB> ways to choose four buttons in +order. For the <CODE>x x x x</CODE> pattern, this is the answer. For the other +patterns, this number (120) has to be divided by various factors to account +for the fact that the order is <EM>partially</EM> immaterial, just as in +deriving the formula for combinations from the formula for permutations we +divided by <EM>r</EM>! because the order is completely immaterial. Consider the +pattern <CODE>x-x x x</CODE>. In this pattern the order of the first two numbers +is immaterial, but the choice of the first two numbers as a pair matters, +and so does the order of the last two numbers. So <CODE>1-2 3 4</CODE> is the same +combination as <CODE>2-1 3 4</CODE> but different from <CODE>1-3 2 4</CODE> or <CODE> +1-2 4 3</CODE>. That means the number 120 is too big by a factor of 2, because +every significant choice of combination is represented twice. For this +pattern the number of different combinations is 60. Of course the same +argument applies to the patterns <CODE>x x-x x</CODE> and <CODE>x x x-x</CODE>. + +<P>What about <CODE>x-x x-x</CODE>? In this pattern there are two pairs of positions +within which order doesn't matter. Each combination appears <EM>four</EM> +times in the list of 120; <CODE>1-2 3-4</CODE> is the same as <CODE>1-2 4-3</CODE>, +<CODE>2-1 3-4</CODE>, and <CODE>2-1 4-3</CODE>. So there are 30 significantly different +combinations in this pattern. What about <CODE>x-x-x x</CODE>? In this pattern, +the order of the first three numbers is irrelevant; this means that there +are 3! or 6 appearances of each combination in the 120, so there are 20 +significantly different combinations in this pattern. The general rule is +that for each group of <EM>m</EM> consecutive hyphens in the pattern you must +divide by (<EM>m</EM>+1)! to eliminate duplicates. + +<P>(My approach was to start with permutations and then divide out redundant +ones. Another approach would be to build up the pattern using combinations. +The pattern <CODE>x-x x x</CODE> contains three groups of numbers representing +three "pushes": a group of two and two groups of one. Since this is a +five-button lock, for the first group of two there are <IMG SRC="5choose2.gif"> choices. +(Order doesn't matter within a group.) For the second group there are only +three buttons remaining from which we can choose, so there are <IMG SRC="3choose1.gif"> +choices for that button. Finally, there are <IMG SRC="2choose1.gif"> choices for the +fourth button (the third group). This makes 10×3×2 possible +combinations for this pattern, the same as the 60 we computed the other way. +For the <CODE>x-x x-x</CODE> pattern this method gives <IMG SRC="5c2x3c2.gif"> +or 30 combinations.) + +<P>Having worked all this out, I was ready to write a computer program to count +the total number of combinations. The trickiest part was deciding how to +deal with the binary numbers that represent the patterns. In the end I used +plain old numbers. The expression + +<P><PRE>remainder :number 2 +</PRE> + +<P>yields the rightmost bit of a number, and then <CODE>:number/2</CODE> +gives all but the rightmost bit (with a little extra effort for odd numbers). +To help you read the program, here is a description of the most important +procedures: + +<P> +<TABLE><TR><TH align="right" valign="top"><CODE>lock 5</CODE><TD> <TD valign="top">outputs the total number of combinations +for the 5-button lock. +<TR><TH align="right" valign="top"><CODE>lock1 5 4</CODE><TD> <TD valign="top">outputs the number of combinations that use +4 out of the 5 buttons. +<TR><TH align="right" valign="top"><CODE>lock2 120 5 1</CODE><TD> <TD valign="top">outputs the number of combinations for the +4-button pattern corresponding to the binary +form of the number 5 (101 or x-x x-x). The +120 is <SUB><SMALL>5</SMALL></SUB><EM>P</EM><SUB><SMALL>4</SMALL></SUB> and the 1 is always used as +the third input except in recursive calls. + +<P></TABLE> + +<P>Here is the program: + +<P><PRE>to lock :buttons +output cascade :buttons [? + lock1 :buttons #] 1 +end + +to lock1 :total :buttons +localmake "perms perms :total :buttons +output cascade (twoto (:buttons-1)) ~ + [? + lock2 :perms #-1 1] ~ + 0 +end + +to twoto :power +output cascade :power [2 * ?] 1 +end + +to lock2 :perms :links :factor +if equalp :links 0 [output :perms/(fact :factor)] +if equalp (remainder :links 2) 0 ~ + [output lock2 :perms/(fact :factor) :links/2 1] +output lock2 :perms (:links-1)/2 :factor+1 +end +</PRE> + +<P>One slight subtlety is that in <CODE>lock</CODE> the third input to +<CODE>cascade</CODE> is 1 rather than 0 to include the one 0-button combination +that would not otherwise be added in. + +<P><H2>An Inductive Solution</H2> + +<P>When I wrote that program, I was pleased with myself for managing to turn +such a messy solution into executable form, but I wasn't satisfied with +the underlying approach. I wanted something mathematically more elegant. + +<P>What made it possible for me to find the approach I wanted was the chance +discovery that the number of combinations that use all five buttons (541) +is half of the total number of combinations (1082). Could this possibly be +a coincidence, or would that have to be true for any number of buttons? +To see that it has to be true, I used an idea from another branch of +mathematics, <EM>set theory.</EM> A <EM>set</EM> is any collection of things, +in no particular order. One can speak of the set of all the fingers on my +left hand, or the set of all the integers, or the set of all the universities +in cities named Cambridge. Much of the interesting part of set theory has +to do with the properties of infinite sets; for example, it turns out that +the set of all the integers is the same size as the set of all the rational +numbers, but both of these are smaller than the set of irrational numbers. +What does it mean for one infinite set to be the same size as, or to be +larger than, another? The same definition works equally well for finite +sets: Two sets are the same size if they can be placed in +<EM>one-to-one correspondence.</EM> This means that you must exhibit a way to +pair the elements of one set with the elements of the other so that each +element of one has exactly one partner in the other. (A set is larger than +another if they aren't the same size, but a subset of the first is the same +size as the second.) + +<P>To prove that my observation about the lock combinations has to be true +regardless of the number of buttons, I have to exhibit a one-to-one +correspondence between two sets: the set of all combinations using all +the buttons of an <EM>n</EM>-button lock and the set of all combinations using +fewer than <EM>n</EM> of the buttons. But that's easy. Starting with a +combination that uses all the buttons, just eliminate the last push (one or +more buttons pushed at the same time) to get a combination using fewer than +all the buttons. For example, for a five-button lock, the five-button +combination <CODE>2 3-4 1-5</CODE> is paired with the three-button combination +<CODE>2 3-4</CODE>. (We have to eliminate the last <EM>push</EM> and not merely +the last <EM>button</EM> for two reasons. First, if we always eliminated +exactly one button, we'd always get a four-button combination, and we want +to pair five-button combinations with all the fewer-than-five ones. +Second, which is the "last" button if the last push involves more than +one? Remember, <CODE>2 3-4 1-5</CODE> is the <EM>same</EM> combination as +<CODE>2 3-4 5-1</CODE>. But writing this combination in two different forms +seems to pair it with two different smaller ones. The rules of one-to-one +correspondence say that each element of a set must have exactly one partner +in the other set.) + +<P>To show that the correspondence works in both directions, start with a +combination that doesn't use all the buttons; its partner is formed by +adding one push at the end that contains all the missing buttons. +For example, if we start with <CODE>1 2-5</CODE> then its partner is +<CODE>1 2-5 3-4</CODE>. + +<P>I've just proved that the number of all-<EM>n</EM> combinations must be equal to +the number of fewer-than-<EM>n</EM> combinations. So it's not a coincidence that +541 is half of 1082. In order to be able to talk about these numbers more +succinctly, I want to define +<P><CENTER><EM>f</EM>(<EM>n</EM>) = number of <EM>n</EM>-button +combinations of an <EM>n</EM>-button lock</CENTER><P> +We've just proved that it's also true that +<P><CENTER><EM>f</EM>(<EM>n</EM>) = number of fewer-than-<EM>n</EM>-button +combinations</CENTER><P> +Now, what does "fewer than <EM>n</EM> buttons" mean? Well, there are +combinations using no buttons, one button, two buttons, and so on up to <EM>n</EM>−1 +buttons. Let's define +<P><CENTER><EM>g</EM>(<EM>n</EM>,<EM>i</EM>) = number of <EM>i</EM>-button +combinations in an <EM>n</EM>-button lock</CENTER><P> +So we can formalize the phrase "fewer than <EM>n</EM>" by saying +<P><CENTER><EM>f</EM>(<EM>n</EM>) = +<EM>g</EM>(<EM>n</EM>,0)+<EM>g</EM>(<EM>n</EM>,1)+<EM>g</EM>(<EM>n</EM>,2)+ ··· +<EM>g</EM>(<EM>n</EM>,<EM>n</EM>−1)</CENTER><P> +Instead of using those dots in the middle, mathematicians have another +notation for a sum of several terms like this. +<P><CENTER><IMG SRC="math26.gif" ALT="math display"></CENTER><P> +If you haven't seen this notation before, the Σ (<EM>sigma</EM>) +symbol is the Greek letter <EM>S,</EM> and is used to represent a <EM>S</EM>um. +It works a little like the <CODE>for</CODE> iteration tool; the variable below the +Σ (in this case, <EM>i</EM>) takes on values from the lower limit (0) to the +upper limit (<EM>n</EM>−1), and for each of those values the expression following the +Σ is added into the sum. The Logo equivalent would be + +<P><PRE>for [i 0 [:n-1]] [make "sum :sum + (g :n :i)] +</PRE> + +<P>The Σ-expression is pronounced "the sum from <EM>i</EM> equals +zero to <EM>n</EM> minus one of <EM>g</EM> of <EM>n</EM> comma <EM>i</EM>." + +<P>So far, what I've done is like what I did before: dividing the set of all +possible combinations into subsets based on the number of buttons used in +each combination. This is like the definition of <CODE>lock</CODE> in terms of +<CODE>lock1</CODE>. The next step is to see if we can find a formula for <EM>g</EM>(<EM>n</EM>,<EM>i</EM>). +How many 3-button combinations, for example, can we make using a 5-button +lock? (That's <EM>g</EM>(5,3).) There are many different ways in which I might +try to derive a formula, but I think it will be helpful at this point to +step back and consider my overall goal. I started this line of reasoning +because I'm trying to express the solution for the five-button lock in terms +of easier solutions for smaller numbers of buttons. That is, I'm looking +for an inductive definition of <EM>f</EM>(<EM>n</EM>) in terms of values of <EM>f</EM> for smaller +arguments. I'd like to end up with a formula like +<P><CENTER><EM>f</EM>(<EM>n</EM>) = ... <EM>f</EM>(0) ... <EM>f</EM>(1) +... <EM>f</EM>(<EM>n</EM>−1) ...</CENTER><P> +but I don't yet know exactly what form it will take. So far I've written +a formula for <EM>f</EM>(<EM>n</EM>) in terms of <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) for values of <EM>i</EM> less than <EM>n</EM>. +It would be great, therefore, if I could express <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) in terms of +<EM>f</EM>(<EM>i</EM>); that would give me exactly what I want. + +<P>To put that last sentence into words, it would be great if I could express +the number of <EM>i</EM>-button combinations of an <EM>n</EM>-button lock in terms of the +number of <EM>i</EM>-button combinations of an <EM>i</EM>-button lock. For example, can I +express the number of combinations using 3 out of 5 buttons in terms of the +number of combinations of 3 out of 3 buttons? Yes, I can. The latter is +the number of rearrangements of three buttons once we've selected the three +buttons. If we start with five buttons, there are <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/5choose3.gif"> possible +sets of three buttons to choose. For each of those <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/5choose3.gif"> sets of +three buttons, there are <EM>f</EM>(3) ways to arrange those three buttons in a +combination. + +<P> + +<P><P><CENTER><IMG SRC="math28.gif" ALT="math display"></CENTER><P> +It may not be obvious why this is so. Suppose you list all the 3-button +combinations of a 3-button lock. There are 13 of them, consisting of the +numbers from 1 to 3 in various orders and with various groups connected +by hyphens. Those 13 combinations are also some of the 3-button combinations +of a 5-button lock, namely, the ones in which the particular three buttons +we chose are 1, 2, and 3. If instead we choose a different set of three +(out of five) buttons, that gives rise to a different set of 13 combinations. +For example, if we choose the buttons 2, 3, and 4, we can take the original +13 combinations and change all the 1s to 2s, all the 2s to 3s, and all the +3s to 4s: + +<P><PRE>buttons: 1,2,3 2,3,4 1,4,5 + + 1 2 3 2 3 4 1 4 5 + 1 3 2 2 4 3 1 5 4 + 2 1 3 3 2 4 4 1 5 + 2 3 1 3 4 2 4 5 1 + 3 1 2 4 2 3 5 1 4 + 3 2 1 4 3 2 5 4 1 + 1 2-3 2 3-4 1 4-5 + 2 1-3 3 2-4 4 1-5 + 3 1-2 4 2-3 5 1-4 + 1-2 3 2-3 4 1-4 5 + 1-3 2 2-4 3 1-5 4 + 2-3 1 3-4 2 4-5 1 + 1-2-3 2-3-4 1-4-5 +</PRE> + +<P>This table has a column for each of three possible combinations of +five numbers three at a time. The table could be extended to have a column +for <EM>every</EM> such combination of numbers, and then it would contain all +the lock combinations using three out of five buttons. The total number of +entries in the extended table is therefore <EM>g</EM>(5,3); the table has <EM>f</EM>(3) +rows and <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/5choose3.gif"> columns. So +<P><CENTER><IMG SRC="math29.gif" ALT="math display"></CENTER><P> +which is a particular case of the general formula above. + +<P>We now have a formula for <EM>f</EM>(<EM>n</EM>) in terms of all the <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) and a formula +for <EM>g</EM>(<EM>n</EM>,<EM>i</EM>) in terms of <EM>f</EM>(<EM>i</EM>). Combining these we have +<P><CENTER><IMG SRC="math30.gif" ALT="math display"></CENTER><P> +or +<P><CENTER><IMG SRC="math31.gif" ALT="math display"></CENTER><P> +Like any inductive definition, this one needs a special rule for the +smallest case, from which all the others are computed: +<P><CENTER><EM>f</EM>(0) = 1</CENTER><P> + +<P>The total number of combinations for an <EM>n</EM>-button lock is 2×<EM>f</EM>(<EM>n</EM>). +I find this much more elegant than my original solution. (So why didn't I +just show you this one to begin with? Because I never would have figured +this one out had I not first done the enumeration of cases. I want you to +see how a combinatorics problem is solved, not just what the beautiful +solution looks like.) This formula can also be turned into a computer +program: + +<P><PRE>to simplex :buttons +output 2 * f :buttons +end + +to f :n +if equalp :n 0 [output 1] +output cascade :n [? + ((choose :n (#-1)) * f (#-1))] 0 +end + +to choose :n :r +output (perms :n :r)/(fact :r) +end +</PRE> + +<P>This program is faster as well as simpler than the other; on my +home computer, <CODE>lock 5</CODE> takes about 4 seconds, <CODE>simplex 5</CODE> about 2 seconds. + +<P>The <CODE>simplex</CODE> function has no exact closed form equivalent, but it turns +out that there is (amazingly!) a closed form definition that, when rounded +to the nearest integer, gives the desired value: + +<P><PRE>to simp :n +output round (fact :n)/(power (ln 2) (:n+1)) +end +</PRE> + +<P>The <CODE>ln</CODE> function, a Logo primitive, computes the "natural +logarithm" of its input; <CODE>ln 2</CODE> has the approximate value 0.69314718056. +The <CODE>power</CODE> function of two inputs takes +the first input to the power of the second input. <CODE>Fact</CODE> is the +factorial function as defined earlier in this chapter. + +<P>Another related programming problem is to list the actual combinations, +rather than merely count them. Probably the simplest way to do that is +to use an approach similar to the one I used in the <CODE>combs</CODE> procedure +that lists combinations of members of a list: First use recursion to +find the lock combinations using only the <CODE>butfirst</CODE> of the available +buttons, then find the ways in which the <CODE>first</CODE> button can be added +to each of them. + +<P><H2>Multinomial Coefficients</H2> + + +<P>Earlier, in talking about Pascal's Triangle, I showed how binomial +coefficients are related to combinations and asked you to think about +<EM>trinomial</EM> coefficients. What, for example, is the coefficient of +<EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM> in the expansion of (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>)<SUP><SMALL>4</SMALL></SUP>? + +<P>The expansion is a sum of products; each of those products contains four +variables (<EM>aaaa</EM>, <EM>aaab</EM>, etc.). The ones that contribute to the <EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM> +term are the ones with one <EM>A</EM>, two <EM>B</EM>s, and one <EM>c</EM>; these include +<EM>abbc</EM>, <EM>bcab</EM>, <EM>cabb</EM>, and so on. Out of the four slots for variables in +one of those products, how many ways can we choose a slot for one <EM>A</EM>? The +answer is <IMG SRC="4choose1.gif">. Having chosen one, we are left with three slots +and we want to choose two of them for <EM>B</EM>s. There are <IMG SRC="3choose2.gif"> ways to +do that. Then we have one slot left, just enough for the one <EM>c</EM>, which +makes a trivial contribution of <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/1choose1.gif"> to the overall number of +possibilities. The total is <IMG SRC="4c1x3c2x1c1.gif"> or 4×3×1 or 12, and that is the coefficient of +<EM>a</EM><EM>b</EM><SUP><SMALL>2</SMALL></SUP><EM>c</EM>. Similarly, the coefficient of <EM>ac</EM><SUP><SMALL>3</SMALL></SUP> is <IMG SRC="4c1x3c3.gif"> or 4. + +<P>The same sort of argument can be used for even more complicated cases. In +the expansion of (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>+<EM>d</EM>+<EM>e</EM>)<SUP><SMALL>14</SMALL></SUP> what is the coefficient of <EM>a</EM><SUP><SMALL>2</SMALL></SUP><EM>b</EM><SUP><SMALL>3</SMALL></SUP><EM>c</EM><EM>d</EM><SUP><SMALL>5</SMALL></SUP><EM>e</EM><SUP><SMALL>3</SMALL></SUP>? +It's <P><CENTER><IMG SRC="math33.gif" ALT="math display"></CENTER><P> + +<P>Here is a harder question: How many terms are there in, say, (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>+<EM>d</EM>)<SUP><SMALL>7</SMALL></SUP>? +It's easy to see that there are 4<SUP><SMALL>7</SMALL></SUP> products of four variables, but after +the ones that are equal to each other have been combined into terms, how +many distinct terms are there? + +<P>Like the Simplex lock problem, this one can probably be solved most easily +by reducing the problem to a smaller subproblem--in other words, by an +inductive definition. This problem also has something in common with the +earlier problem of listing all the combinations of a given size from a +given list, as we did in the <CODE>combs</CODE> procedure. Try to solve the +problem before reading further. (It's hard to say how another person will +find a problem, but I think this one is easier than the Simplex one.) + +<P>In order to be able to express the original problem in terms of a smaller +version, we have to generalize it. I posed a specific problem, about the +seventh power of the sum of four variables. I'd like to be able to give +the answer to that problem the name <EM>t</EM>(4,7) and try to find a way to +express that in terms of, let's say, <EM>t</EM>(4,6). So I'm going to define +the function <EM>t</EM> as +<P><CENTER><EM>t</EM>(<EM>n</EM>,<EM>k</EM>) = number of terms +in (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>+<EM>a</EM><SUB><SMALL>2</SMALL></SUB>+ + ··· ++<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL><EM>k</EM></SMALL></SUP></CENTER><P> +(If this were a "straight" math book I'd cheerfully recycle the name <EM>f</EM> +for the function, even though we had a different <EM>f</EM> in the last section, +but I'm anticipating wanting to write a Logo program for this problem and I +can't have two procedures named <CODE>f</CODE> in the same workspace.) + +<P>In writing <CODE>combs</CODE> I used the trick of dividing all possible +combinations into two groups: those including the first member of the list +and those not including that member. A similar trick will be useful here; +we can divide all the terms in an expansion into two groups. One group will +contain those terms that include the first variable (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>) and the other +will contain the rest. For example, in the original problem, <EM>a</EM><SUP><SMALL>2</SMALL></SUP><EM>b</EM><SUP><SMALL>3</SMALL></SUP><EM>d</EM><SUP><SMALL>2</SMALL></SUP> is +a term in the first group, while <EM>c</EM><SUP><SMALL>7</SMALL></SUP> is a term in the second group. + +<P>A term in the first group can be divided by <EM>a</EM><SUB><SMALL>1</SMALL></SUB>; the result must be a term +in the expansion of (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>+<EM>a</EM><SUB><SMALL>2</SMALL></SUB>+ ··· +<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL><EM>k</EM>−1</SMALL></SUP>. How many such terms are +there? There are <EM>t</EM>(<EM>n</EM>,<EM>k</EM>−1) of them. So that's how many terms there are in +the first group. + +<P>A term in the second group is a product of <EM>k</EM> variables <EM>not</EM> +including <EM>a</EM><SUB><SMALL>1</SMALL></SUB>. That means that such a term is also part of the expansion +of (<EM>a</EM><SUB><SMALL>2</SMALL></SUB>+ ··· +<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL><EM>k</EM></SMALL></SUP>. How many such terms are there? There are +<EM>t</EM>(<EM>n</EM>−1,<EM>k</EM>) of them. Notice the difference between the two groups. In the +first case, we associate a term with a similar term in the expansion of an +expression involving a <EM>smaller power</EM> of the <EM>same number</EM> of +variables. In the second case, we associate a term with an equal term in +the expansion of an expression involving <EM>fewer variables</EM> taken to +the <EM>same power.</EM> + +<P>Combining these two results, we see that +<P><CENTER><EM>t</EM>(<EM>n</EM>,<EM>k</EM>) = +<EM>t</EM>(<EM>n</EM>,<EM>k</EM>−1)+<EM>t</EM>(<EM>n</EM>−1,<EM>k</EM>)</CENTER><P> +Since this is a function of two variables, it needs two "stop rules," just +like the function <IMG SRC="nchooser.gif">. Picking these limiting cases seems much +simpler than inventing the induction rule, but even so, it may repay some +attention. For the rule +<P><CENTER><IMG SRC="math36.gif" ALT="math display"></CENTER><P> +we ended up considering the limiting cases <EM>r</EM>=0 and <EM>r</EM>=<EM>n</EM>. I didn't say +anything about it at the time because I didn't want to get distracted, but +it's not obvious why there is the asymmetry between the two variables in +those limiting cases. That is, why didn't I pick <EM>r</EM>=0 and <EM>n</EM>=0 as the +limiting cases? That would be more like what you're accustomed to in +recursive Logo procedures, where stop rules almost always involve a +comparison of something with zero or with the empty list. + +<P>The funny limiting cases for <IMG SRC="nchooser.gif"> (and the corresponding funny stop +rules in <CODE>combs</CODE>) are related to the fact that this function is +meaningful only when <EM>n</EM>≥<EM>r</EM>. The two arguments can't be chosen +independently. If we didn't have the <EM>r</EM>=<EM>n</EM> limiting case, the inductive +formula would have us compute +<P><CENTER><IMG SRC="math37.gif" ALT="math display"></CENTER><P> +If we define <IMG SRC="https://people.eecs.berkeley.edu/~bh/v3ch2/4choose5.gif"> as zero, this equation does turn out to be true, +but it isn't a very sensible way to compute <IMG SRC="5choose5.gif">. + +<P>In the case of the function <EM>t</EM>, the two arguments <EM>are</EM> independent. +Both <EM>t</EM>(4,7) and <EM>t</EM>(7,4) are sensible things to ask for. Therefore, we +should use the more obvious limiting cases <EM>n</EM>=0 and <EM>k</EM>=0. The trouble is +that it's not obvious what the value of <EM>t</EM>(0,<EM>k</EM>) or <EM>t</EM>(<EM>n</EM>,0) should be. The +first of these, <EM>t</EM>(0,<EM>k</EM>), represents the number of terms in the expansion of +()<SUP><SMALL><EM>k</EM></SMALL></SUP>--nothing to the <EM>k</EM>th power! That seems meaningless. On the other +hand, <EM>t</EM>(<EM>n</EM>,0) represents the number of terms in (∑ <EM>a</EM><SUB><SMALL><EM>i</EM></SMALL></SUB>)<SUP><SMALL>0</SMALL></SUP>, which is 1. +Anything to the zeroth power is 1. Does "1" count as a term? It doesn't +have any variables in it. + +<P> + +<P>One solution would be to take as limiting cases <EM>n</EM>=1 and <EM>k</EM>=1. It's much +easier to see what those values should be. (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>)<SUP><SMALL><EM>k</EM></SMALL></SUP> has one term, so +<EM>t</EM>(1,<EM>k</EM>)=1. And (<EM>a</EM><SUB><SMALL>1</SMALL></SUB>+ ··· +<EM>a</EM><SUB><SMALL><EM>n</EM></SMALL></SUB>)<SUP><SMALL>1</SMALL></SUP> has <EM>n</EM> terms, so <EM>t</EM>(<EM>n</EM>,1)=<EM>n</EM>. We +could, then, define the function <EM>t</EM> as +<P><CENTER><IMG SRC="math38.gif" ALT="math display"></CENTER><P> +But it is possible to figure out appropriate values for zero arguments by +working backwards from the cases we already understand. For example, we +know that <EM>t</EM>(2,1) must equal 2. But +<P><CENTER><EM>t</EM>(2,1) = <EM>t</EM>(2,0)+<EM>t</EM>(1,1) = <EM>t</EM>(2,0)+1</CENTER><P> +It follows that <EM>t</EM>(2,0) must be 1. So it's reasonable to guess that +<EM>t</EM>(<EM>n</EM>,0)=1 will work in general. Similarly, we know that <EM>t</EM>(1,2)=1, but +<P><CENTER><EM>t</EM>(1,2) = <EM>t</EM>(1,1)+<EM>t</EM>(0,2) = 1+<EM>t</EM>(2,0)</CENTER><P> +Therefore <EM>t</EM>(0,2) must be 0. We can define <EM>t</EM> as +<P><CENTER><IMG SRC="math41.gif" ALT="math display"></CENTER><P> + +<P>What is <EM>t</EM>(0,0)? The definition above contradicts itself about this. The +answer should be 0 because <EM>n</EM>=0 but also 1 because <EM>k</EM>=0. This reminds me +of the similar problem about powers of integers. What is 0<SUP><SMALL>0</SMALL></SUP>? In general +0<SUP><SMALL><EM>x</EM></SMALL></SUP>=0 but <EM>x</EM><SUP><SMALL>0</SMALL></SUP>=1, for nonzero <EM>x</EM>. There is really no "right" answer, +but mathematicians have adopted the convention that 0<SUP><SMALL>0</SMALL></SUP>=1. To make our +definition of <EM>t</EM> truly correct I have to choose a convention for <EM>t</EM>(0,0) +and modify the definition to reflect it: +<P><CENTER><IMG SRC="math42.gif" ALT="math display"></CENTER><P> + +<P> + +<P>It's straightforward to translate this mathematical function definition into +a Logo procedure: + +<P><PRE>to t :n :k +if equalp :k 0 [output 1] +if equalp :n 0 [output 0] +output (t :n :k-1)+(t :n-1 :k) +end +</PRE> + +<P>Using this function we can compute <CODE>t 4 7</CODE> and find that the +answer to the original problem is 120. + +<P>(Can you write a program to display the actual expansion? That is, it +should print something like + +<P><PRE>(A+B+C+D)^7 = + 1 A^7 + + 7 A^6 B + + 21 A^5 B^2 + + ... +</PRE> + +<P>There are two parts to this problem. One is to figure out the +combinations of variables in the 120 terms, which can be done with a +procedure like <CODE>combs</CODE>, and the other is to figure out the coefficients, +which I discussed at the beginning of this section.) + +<P>I was introduced to this problem as a student teacher in a high school +probability class. The teacher gave "how many terms are there in the +expansion of (<EM>a</EM>+<EM>b</EM>+<EM>c</EM>+<EM>d</EM>)<SUP><SMALL>7</SMALL></SUP>" as a quiz problem, and nobody answered it. +In the ensuing class discussion, it turned out that she meant the students +to answer the much easier question of how many products of seven variables +there are. As I noted earlier, the answer to <EM>that</EM> question is just +4<SUP><SMALL>7</SMALL></SUP>. But all the students interpreted the question as meaning the harder +one we've been exploring here. I took the problem home that evening and +reached the point we've reached in this chapter. I didn't think I could get +a better answer than that until my housemate taught me about +generating functions. It turns out that there <EM>is</EM> a +closed form definition for +this function: +<P><CENTER><IMG SRC="math43.gif" ALT="math display"></CENTER><P> +This definition is faster to compute as well as more beautiful. + +<P>Once armed with the formula, it wasn't hard to invent a way to demonstrate +that it must be correct without going through the inductive definition and +the use of calculus. The trick is that we must be choosing <EM>n</EM>−1 somethings +out of a possible <EM>k</EM>+<EM>n</EM>−1 for each term. What does a term look like? +Ignoring the constant coefficient, it is the product of <EM>k</EM> (seven, in the +specific problem given) variables, some of which may be equal. Furthermore, +when the terms are written in the usual way, the variables come in +alphabetical order. A term like <EM>a</EM><SUP><SMALL>2</SMALL></SUP><EM>b</EM><SUP><SMALL>4</SMALL></SUP><EM>d</EM> represents <EM>aabbbbd</EM>; there won't +be a different term with the same letters in another order. In general, the +<EM>k</EM> variables will be some number (zero or more) of <EM>a</EM><SUB><SMALL>1</SMALL></SUB>s, then some number +of <EM>a</EM><SUB><SMALL>2</SMALL></SUB>s, and so on. + +<P>Now comes the trick. Suppose we write the string of variables with a +"wall" for each change to the next letter. So instead of <EM>aabbbbd</EM> I want +to write <EM>aa</EM>|<EM>bbbb</EM>||<EM>d</EM>. (There are two walls before the +final <EM>d</EM> to reflect the fact that we skipped over <EM>c</EM>.) In this notation +there are always exactly <EM>n</EM>−1 walls. (That's why I chose to put the walls +in; remember, we're looking for <EM>n</EM>−1 of something.) The term includes <EM>k</EM> +variables and <EM>n</EM>−1 walls, for a total of <EM>k</EM>+<EM>n</EM>−1 symbols. + +<P>Once the walls are there, it really is no longer necessary to preserve the +individual variable letters. The sample term we've been using could just as +well be written <EM>xx</EM>|<EM>xxxx</EM>||<EM>x</EM>. What comes before the first +wall is the first variable letter, and so on. So ||<EM>xxx</EM>|<EM>xxxx</EM> represents <EM>c</EM><SUP><SMALL>3</SMALL></SUP><EM>d</EM><SUP><SMALL>4</SMALL></SUP>. But now we're finished. We have found a way to +represent each possible term as a string of <EM>k</EM> copies of the letter <EM>x</EM> +interspersed with <EM>n</EM>−1 walls. How many such arrangements are there? How +many ways are there to choose <EM>n</EM>−1 positions for walls in a string of +<EM>k</EM>+<EM>n</EM>−1 symbols? + +<P>Earlier, in talking about the difference between closed form and inductive +definitions, I suggested that the an inductive definition might be much +easier to discover even if a closed form definition also exists. This is a +clear example. If I'd given the demonstration just above, with <EM>x</EM>s and +walls, without first showing you the more roundabout way I really discovered +the definition, you'd rightly complain about rabbits out of hats. + +<P> +<TABLE width="100%"><TR><TD><A HREF="../v3-toc2.html">(back to Table of Contents)</A> +<TD align="right"><A HREF="../v3ch1/v3ch1.html"><STRONG>BACK</STRONG></A> +chapter thread <A HREF="../v3ch3/v3ch3.html"><STRONG>NEXT</STRONG></A> +</TABLE> + +<P><H2>Program Listing</H2> + +<P><P> +<P><PRE> +;;; Logic problem inference system + +;; Establish categories + +to category :category.name :members +print (list "category :category.name :members) +if not namep "categories [make "categories []] +make "categories lput :category.name :categories +make :category.name :members +foreach :members [pprop ? "category :category.name] +end + +;; Verify and falsify matches + +to verify :a :b +settruth :a :b "true +end + +to falsify :a :b +settruth :a :b "false +end + +to settruth :a :b :truth.value +if equalp (gprop :a "category) (gprop :b "category) [stop] +localmake "oldvalue get :a :b +if equalp :oldvalue :truth.value [stop] +if equalp :oldvalue (not :truth.value) ~ + [(throw "error (sentence [inconsistency in settruth] + :a :b :truth.value))] +print (list :a :b "-> :truth.value) +store :a :b :truth.value +settruth1 :a :b :truth.value +settruth1 :b :a :truth.value +if not emptyp :oldvalue ~ + [foreach (filter [equalp first ? :truth.value] :oldvalue) + [apply "settruth butfirst ?]] +end + +to settruth1 :a :b :truth.value +apply (word "find not :truth.value) (list :a :b) +foreach (gprop :a "true) [settruth ? :b :truth.value] +if :truth.value [foreach (gprop :a "false) [falsify ? :b] + pprop :a (gprop :b "category) :b] +pprop :a :truth.value (fput :b gprop :a :truth.value) +end + +to findfalse :a :b +foreach (filter [not equalp get ? :b "true] peers :a) ~ + [falsify ? :b] +end + +to findtrue :a :b +if equalp (count peers :a) (1+falses :a :b) ~ + [verify (find [not equalp get ? :b "false] peers :a) + :b] +end + +to falses :a :b +output count filter [equalp "false get ? :b] peers :a +end + +to peers :a +output thing gprop :a "category +end + +;; Common types of clues + +to differ :list +print (list "differ :list) +foreach :list [differ1 ? ?rest] +end + +to differ1 :a :them +foreach :them [falsify :a ?] +end + +to justbefore :this :that :lineup +falsify :this :that +falsify :this last :lineup +falsify :that first :lineup +justbefore1 :this :that :lineup +end + +to justbefore1 :this :that :slotlist +if emptyp butfirst :slotlist [stop] +equiv :this (first :slotlist) :that (first butfirst :slotlist) +justbefore1 :this :that (butfirst :slotlist) +end + +;; Remember conditional linkages + +to implies :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +implies1 :who2 :what2 (not :truth2) :who1 :what1 (not :truth1) +end + +to implies1 :who1 :what1 :truth1 :who2 :what2 :truth2 +localmake "old1 get :who1 :what1 +if equalp :old1 :truth1 [settruth :who2 :what2 :truth2 stop] +if equalp :old1 (not :truth1) [stop] +if memberp (list :truth1 :who2 :what2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +if memberp (list :truth1 :what2 :who2 (not :truth2)) :old1 ~ + [settruth :who1 :what1 (not :truth1) stop] +store :who1 :what1 ~ + fput (list :truth1 :who2 :what2 :truth2) :old1 +end + +to equiv :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "true +implies :who2 :what2 "true :who1 :what1 "true +end + +to xor :who1 :what1 :who2 :what2 +implies :who1 :what1 "true :who2 :what2 "false +implies :who1 :what1 "false :who2 :what2 "true +end + +;; Interface to property list mechanism + +to get :a :b +output gprop :a :b +end + +to store :a :b :val +pprop :a :b :val +pprop :b :a :val +end + +;; Print the solution + +to solution +foreach thing first :categories [solve1 ? butfirst :categories] +end + +to solve1 :who :order +type :who +foreach :order [type "| | type gprop :who ?] +print [] +end + +;; Get rid of old problem data + +to cleanup +if not namep "categories [stop] +ern :categories +ern "categories +erpls +end + +;; Anita Harnadek's problem + +to cub.reporter +cleanup +category "first [Jane Larry Opal Perry] +category "last [Irving King Mendle Nathan] +category "age [32 38 45 55] +category "job [drafter pilot sergeant driver] +differ [Jane King Larry Nathan] +says "Jane "Irving 45 +says "King "Perry "driver +says "Larry "sergeant 45 +says "Nathan "drafter 38 +differ [Mendle Jane Opal Nathan] +says "Mendle "pilot "Larry +says "Jane "pilot 45 +says "Opal 55 "driver +says "Nathan 38 "driver +print [] +solution +end + +to says :who :what1 :what2 +print (list "says :who :what1 :what2) +xor :who :what1 :who :what2 +end + +;; Diane Baldwin's problem + +to foote.family +cleanup +category "when [1st 2nd 3rd 4th 5th] +category "name [Felix Fred Frank Francine Flo] +category "street [Field Flag Fig Fork Frond] +category "item [food film flashlight fan fiddle] +category "position [1 2 3 4 5] +print [Clue 1] +justbefore "Flag "2nd :position +justbefore "2nd "Fred :position +print [Clue 2] +male [film Fig 5th] +print [Clue 3] +justbefore "flashlight "Fork :position +justbefore "Fork "1st :position +female [1st] +print [Clue 4] +falsify "5th "Frond +falsify "5th "fan +print [Clue 5] +justbefore "Francine "Frank :position +justbefore "Francine "Frank :when +print [Clue 6] +female [3rd Flag] +print [Clue 7] +justbefore "fiddle "Frond :when +justbefore "Flo "fiddle :when +print [] +solution +end + +to male :stuff +differ sentence :stuff [Francine Flo] +end + +to female :stuff +differ sentence :stuff [Felix Fred Frank] +end + +;;; Combinatorics toolkit + +to combs :list :howmany +if equalp :howmany 0 [output [[]]] +if equalp :howmany count :list [output (list :list)] +output sentence (map [fput first :list ?] + combs (butfirst :list) (:howmany-1)) ~ + (combs (butfirst :list) :howmany) +end + +to fact :n +output cascade :n [# * ?] 1 +end + +to perms :n :r +if equalp :r 0 [output 1] +output :n * perms :n-1 :r-1 +end + +to choose :n :r +output (perms :n :r)/(fact :r) +end + +;; The socks problem + +to socks :list +localmake "total combs (expand :list) 2 +localmake "matching filter [equalp first ? last ?] :total +print (sentence [there are] count :total [possible pairs of socks.]) +print (sentence [of these,] count :matching [are matching pairs.]) +print sentence [probability of match =] ~ + word (100 * (count :matching)/(count :total)) "% +end + +to expand :list +if emptyp :list [output []] +if numberp first :list ~ + [output cascade (first :list) + [fput first butfirst :list ?] + (expand butfirst butfirst :list)] +output fput first :list expand butfirst :list +end + +to socktest +localmake "first pick [brown brown brown brown brown brown + blue blue blue blue] +localmake "second ~ + pick (ifelse equalp :first "brown ~ + [[brown brown brown brown brown + blue blue blue blue]] ~ + [[brown brown brown brown brown brown + blue blue blue]]) +output equalp :first :second +end + +;; The Simplex lock problem + +to lock :buttons +output cascade :buttons [? + lock1 :buttons #] 1 +end + +to lock1 :total :buttons +local "perms +make "perms perms :total :buttons +output cascade (twoto (:buttons-1)) [? + lock2 :perms #-1 1] 0 +end + +to lock2 :perms :links :factor +if equalp :links 0 [output :perms/(fact :factor)] +if equalp (remainder :links 2) 0 ~ + [output lock2 :perms/(fact :factor) :links/2 1] +output lock2 :perms (:links-1)/2 :factor+1 +end + +to twoto :power +output cascade :power [2 * ?] 1 +end + +to simplex :buttons +output 2 * f :buttons +end + +to f :n +if equalp :n 0 [output 1] +output cascade :n [? + ((choose :n (#-1)) * f (#-1))] 0 +end + +to simp :n +output round (fact :n)/(power (ln 2) (:n+1)) +end + +;; The multinomial expansion problem + +to t :n :k +if equalp :k 0 [output 1] +if equalp :n 0 [output 0] +output (t :n :k-1)+(t :n-1 :k) +end +</PRE><P> + + + +<P><A HREF="../v3-toc2.html">(back to Table of Contents)</A> +<P><A HREF="../v3ch1/v3ch1.html"><STRONG>BACK</STRONG></A> +chapter thread <A HREF="../v3ch3/v3ch3.html"><STRONG>NEXT</STRONG></A> + +<P> +<ADDRESS> +<A HREF="../index.html">Brian Harvey</A>, +<CODE>bh@cs.berkeley.edu</CODE> +</ADDRESS> +</BODY> +</HTML> |
