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340 lines
15 KiB
Markdown
340 lines
15 KiB
Markdown
---
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language: prolog
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filename: learnprolog.pl
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contributors:
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- ["hyphz", "http://github.com/hyphz/"]
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---
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Prolog is a logic programming language first specified in 1972, and refined into multiple modern implementations.
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```
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% This is a comment.
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% Prolog treats code entered in interactive mode differently
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% to code entered in a file and loaded ("consulted").
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% This code must be loaded from a file to work as intended.
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% Lines that begin with ?- can be typed in interactive mode.
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% A bunch of errors and warnings will trigger when you load this file
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% due to the examples which are supposed to fail - they can be safely
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% ignored.
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% Output is based on SWI-prolog 7.2.3. Different Prologs may behave
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% differently.
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% Prolog is based on the ideal of logic programming.
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% A subprogram (called a predicate) represents a state of the world.
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% A command (called a goal) tells Prolog to make that state of the world
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% come true, if possible.
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% As an example, here is a definition of the simplest kind of predicate:
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% a fact.
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magicNumber(7).
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magicNumber(9).
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magicNumber(42).
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% This introduces magicNumber as a predicate and says that it is true
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% with parameter 7, 9, or 42, but no other parameter. Note that
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% predicate names must start with lower case letters. We can now use
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% interactive mode to ask if it is true for different values:
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?- magicNumber(7). % True
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?- magicNumber(8). % False
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?- magicNumber(9). % True
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% Some older Prologs may display "Yes" and "No" instead of True and
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% False.
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% What makes Prolog unusual is that we can also tell Prolog to _make_
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% magicNumber true, by passing it an undefined variable. Any name
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% starting with a capital letter is a variable in Prolog.
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?- magicNumber(Presto). % Presto = 7 ;
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% Presto = 9 ;
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% Presto = 42.
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% Prolog makes magicNumber true by assigning one of the valid numbers to
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% the undefined variable Presto. By default it assigns the first one, 7.
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% By pressing ; in interactive mode you can reject that solution and
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% force it to assign the next one, 9. Pressing ; again forces it to try
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% the last one, 42, after which it no longer accepts input because this
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% is the last solution. You can accept an earlier solution by pressing .
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% instead of ;.
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% This is Prolog's central operation: unification. Unification is
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% essentially a combination of assignment and equality! It works as
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% follows:
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% If both sides are bound (ie, defined), check equality.
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% If one side is free (ie, undefined), assign to match the other side.
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% If both sides are free, the assignment is remembered. With some luck,
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% one of the two sides will eventually be bound, but this isn't
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% necessary.
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%
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% The = sign in Prolog represents unification, so:
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?- 2 = 3. % False - equality test
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?- X = 3. % X = 3 - assignment
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?- X = 2, X = Y. % X = Y = 2 - two assignments
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% Note Y is assigned too, even though it is
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% on the right hand side, because it is free
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?- X = 3, X = 2. % False
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% First acts as assignment and binds X=3
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% Second acts as equality because X is bound
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% Since 3 does not equal 2, gives False
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% Thus in Prolog variables are immutable
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?- X = 3+2. % X = 3+2 - unification can't do arithmetic
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?- X is 3+2. % X = 5 - "is" does arithmetic.
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?- 5 = X+2. % This is why = can't do arithmetic -
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% because Prolog can't solve equations
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?- 5 is X+2. % Error. Unlike =, the right hand side of IS
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% must always be bound, thus guaranteeing
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% no attempt to solve an equation.
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?- X = Y, X = 2, Z is Y + 3. % X = Y, Y = 2, Z = 5.
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% X = Y are both free, so Prolog remembers
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% it. Therefore assigning X will also
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% assign Y.
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% Any unification, and thus any predicate in Prolog, can either:
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% Succeed (return True) without changing anything,
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% because an equality-style unification was true
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% Succeed (return True) and bind one or more variables in the process,
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% because an assignment-style unification was made true
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% or Fail (return False)
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% because an equality-style unification was false
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% (Failure can never bind variables)
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% The ideal of being able to give any predicate as a goal and have it
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% made true is not always possible, but can be worked toward. For
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% example, Prolog has a built in predicate plus which represents
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% arithmetic addition but can reverse simple additions.
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?- plus(1, 2, 3). % True
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?- plus(1, 2, X). % X = 3 because 1+2 = X.
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?- plus(1, X, 3). % X = 2 because 1+X = 3.
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?- plus(X, 2, 3). % X = 1 because X+2 = 3.
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?- plus(X, 5, Y). % Error - although this could be solved,
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% the number of solutions is infinite,
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% which most predicates try to avoid.
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% When a predicate such as magicNumber can give several solutions, the
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% overall compound goal including it may have several solutions too.
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?- magicNumber(X), plus(X,Y,100). % X = 7, Y = 93 ;
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% X = 9, Y = 91 ;
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% X = 42, Y = 58 .
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% Note: on this occasion it works to pass two variables to plus because
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% only Y is free (X is bound by magicNumber).
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% However, if one of the goals is fully bound and thus acts as a test,
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% then solutions which fail the test are rejected.
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?- magicNumber(X), X > 40. % X = 42
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?- magicNumber(X), X > 100. % False
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% To see how Prolog actually handles this, let's introduce the print
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% predicate. Print always succeeds, never binds any variables, and
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% prints out its parameter as a side effect.
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?- print("Hello"). % "Hello" true.
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?- X = 2, print(X). % 2 true.
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?- X = 2, print(X), X = 3. % 2 false - print happens immediately when
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% it is encountered, even though the overall
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% compound goal fails (because 2 != 3,
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% see the example above).
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% By using Print we can see what actually happens when we give a
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% compound goal including a test that sometimes fails.
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?- magicNumber(X), print(X), X > 40. % 7 9 42 X = 42 .
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% MagicNumber(X) unifies X with its first possibility, 7.
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% Print(X) prints out 7.
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% X > 40 tests if 7 > 40. It is not, so it fails.
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% However, Prolog remembers that magicNumber(X) offered multiple
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% solutions. So it _backtracks_ to that point in the code to try
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% the next solution, X = 9.
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% Having backtracked it must work through the compound goal
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% again from that point including the Print(X). So Print(X) prints out
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% 9.
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% X > 40 tests if 9 > 40 and fails again.
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% Prolog remembers that magicNumber(X) still has solutions and
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% backtracks. Now X = 42.
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% It works through the Print(X) again and prints 42.
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% X > 40 tests if 42 > 40 and succeeds so the result bound to X
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% The same backtracking process is used when you reject a result at
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% the interactive prompt by pressing ;, for example:
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?- magicNumber(X), print(X), X > 8. % 7 9 X = 9 ;
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% 42 X = 42.
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% As you saw above we can define our own simple predicates as facts.
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% More complex predicates are defined as rules, like this:
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nearby(X,Y) :- X = Y.
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nearby(X,Y) :- Y is X+1.
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nearby(X,Y) :- Y is X-1.
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% nearby(X,Y) is true if Y is X plus or minus 1.
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% However this predicate could be improved. Here's why:
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?- nearby(2,3). % True ; False.
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% Because we have three possible definitions, Prolog sees this as 3
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% possibilities. X = Y fails, so Y is X+1 is then tried and succeeds,
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% giving the True answer. But Prolog still remembers there are more
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% possibilities for nearby() (in Prolog terminology, "it has a
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% choice point") even though "Y is X-1" is doomed to fail, and gives us
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% the option of rejecting the True answer, which doesn't make a whole
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% lot of sense.
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?- nearby(4, X). % X = 4 ;
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% X = 5 ;
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% X = 3. Great, this works
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?- nearby(X, 4). % X = 4 ;
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% error
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% After rejecting X = 4 prolog backtracks and tries "Y is X+1" which is
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% "4 is X+1" after substitution of parameters. But as we know from above
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% "is" requires its argument to be fully instantiated and it is not, so
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% an error occurs.
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% One way to solve the first problem is to use a construct called the
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% cut, !, which does nothing but which cannot be backtracked past.
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nearbychk(X,Y) :- X = Y, !.
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nearbychk(X,Y) :- Y is X+1, !.
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nearbychk(X,Y) :- Y is X-1.
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% This solves the first problem:
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?- nearbychk(2,3). % True.
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% But unfortunately it has consequences:
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?- nearbychk(2,X). % X = 2.
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% Because Prolog cannot backtrack past the cut after X = Y, it cannot
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% try the possibilities "Y is X+1" and "Y is X-1", so it only generates
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% one solution when there should be 3.
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% However if our only interest is in checking if numbers are nearby,
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% this may be all we need, thus the name nearbychk.
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% This structure is used in Prolog itself from time to time (for example
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% in list membership).
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% To solve the second problem we can use built-in predicates in Prolog
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% to verify if a parameter is bound or free and adjust our calculations
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% appropriately.
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nearby2(X,Y) :- nonvar(X), X = Y.
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nearby2(X,Y) :- nonvar(X), Y is X+1.
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nearby2(X,Y) :- nonvar(X), Y is X-1.
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nearby2(X,Y) :- var(X), nonvar(Y), nearby2(Y,X).
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% We can combine this with a cut in the case where both variables are
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% bound, to solve both problems.
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nearby3(X,Y) :- nonvar(X), nonvar(Y), nearby2(X,Y), !.
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nearby3(X,Y) :- nearby2(X,Y).
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% However when writing a predicate it is not normally necessary to go to
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% these lengths to perfectly support every possible parameter
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% combination. It suffices to support parameter combinations we need to
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% use in the program. It is a good idea to document which combinations
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% are supported. In regular Prolog this is informally in structured
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% comments, but in some Prolog variants like Visual Prolog and Mercury
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% this is mandatory and checked by the compiler.
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% Here is the structured comment declaration for nearby3:
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%! nearby3(+X:Int, +Y:Int) is semideterministic.
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%! nearby3(+X:Int, -Y:Int) is multi.
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%! nearby3(-X:Int, +Y:Int) is multi.
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% For each variable we list a type. The + or - before the variable name
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% indicates if the parameter is bound (+) or free (-). The word after
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% "is" describes the behaviour of the predicate:
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% semideterministic - can succeed once or fail
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% ( Two specific numbers are either nearby or not )
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% multi - can succeed multiple times but cannot fail
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% ( One number surely has at least 3 nearby numbers )
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% Other possibilities are:
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% det - always succeeds exactly once (eg, print)
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% nondet - can succeed multiple times or fail.
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% In Prolog these are just structured comments and strictly informal but
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% extremely useful.
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% An unusual feature of Prolog is its support for atoms. Atoms are
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% essentially members of an enumerated type that are created on demand
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% whenever an unquoted non variable value is used. For example:
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character(batman). % Creates atom value batman
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character(robin). % Creates atom value robin
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character(joker). % Creates atom value joker
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character(darthVader). % Creates atom value darthVader
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?- batman = batman. % True - Once created value is reused
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?- batman = batMan. % False - atoms are case sensitive
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?- batman = darthVader. % False - atoms are distinct
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% Atoms are popular in examples but were created on the assumption that
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% Prolog would be used interactively by end users - they are less
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% useful for modern applications and some Prolog variants abolish them
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% completely. However they can be very useful internally.
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% Loops in Prolog are classically written using recursion.
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% Note that below, writeln is used instead of print because print is
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% intended for debugging.
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%! countTo(+X:Int) is deterministic.
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%! countUpTo(+Value:Int, +Limit:Int) is deterministic.
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countTo(X) :- countUpTo(1,X).
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countUpTo(Value, Limit) :- Value = Limit, writeln(Value), !.
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countUpTo(Value, Limit) :- Value \= Limit, writeln(Value),
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NextValue is Value+1,
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countUpTo(NextValue, Limit).
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?- countTo(10). % Outputs 1 to 10
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% Note the use of multiple declarations in countUpTo to create an
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% IF test. If Value = Limit fails the second declaration is run.
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% There is also a more elegant syntax.
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%! countUpTo2(+Value:Int, +Limit:Int) is deterministic.
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countUpTo2(Value, Limit) :- writeln(Value),
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Value = Limit -> true ; (
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NextValue is Value+1,
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countUpTo2(NextValue, Limit)).
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?- countUpTo2(1,10). % Outputs 1 to 10
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% If a predicate returns multiple times it is often useful to loop
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% through all the values it returns. Older Prologs used a hideous syntax
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% called a "failure-driven loop" to do this, but newer ones use a higher
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% order function.
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%! countTo2(+X:Int) is deterministic.
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countTo2(X) :- forall(between(1,X,Y),writeln(Y)).
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?- countTo2(10). % Outputs 1 to 10
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% Lists are given in square brackets. Use memberchk to check membership.
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% A group is safe if it doesn't include Joker or does include Batman.
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%! safe(Group:list(atom)) is deterministic.
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safe(Group) :- memberchk(joker, Group) -> memberchk(batman, Group) ; true.
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?- safe([robin]). % True
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?- safe([joker]). % False
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?- safe([joker, batman]). % True
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% The member predicate works like memberchk if both arguments are bound,
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% but can accept free variables and thus can be used to loop through
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% lists.
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?- member(X, [1,2,3]). % X = 1 ; X = 2 ; X = 3 .
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?- forall(member(X,[1,2,3]),
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(Y is X+1, writeln(Y))). % 2 3 4
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% The maplist function can be used to generate lists based on other
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% lists. Note that the output list is a free variable, causing an
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% undefined value to be passed to plus, which is then bound by
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% unification. Also notice the use of currying on the plus predicate -
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% it's a 3 argument predicate, but we specify only the first, because
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% the second and third are filled in by maplist.
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?- maplist(plus(1), [2,3,4], Output). % Output = [3, 4, 5].
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```
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##Ready For More?
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* [SWI-Prolog](http://www.swi-prolog.org/)
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