By George F. Luger, William A Stubblefield

AI Algorithms, info buildings, and Idioms in Prolog, Lisp, and Java

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Extra resources for AI algorithms, data structures, and idioms in Prolog, Lisp, and Java

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For example, likes(george, Y), likes(susie, Y). represents the set of things (or people) liked by BOTH George and Susie. ” This could be stated as: likes(george, kate), likes(george, susie). Likewise, “George likes Kate or George likes Susie”: likes(george, kate); likes(george, susie). Finally, “George likes Susie if George does not like Kate”: likes(george, susie) :- not(likes(george, kate)). pd36 36 5/15/2008 6:34:56 PM Chapter 2 Prolog: Representation 21 These examples show how the predicate calculus connectives are expressed in Prolog.

ObjectOriented Programming in Java Java is the third language considered in this book. Although it does not have Lisp or Prolog’s long historical association with Artificial Intelligence, it has become extremely important as a tool for delivering practical AI applications. There are two primary reasons for this. The first is Java’s elegant, dynamic implementation of object-oriented programming, a programming paradigm with its roots in AI, that has proven its power for use building AI programs through Smalltalk, Flavors, the Common Lisp Object System (CLOS), and other object-oriented systems.

In Horn clause form, the left-hand side (conclusion) of an implication must be a single positive literal. The Horn clause calculus is equivalent to the full first-order predicate calculus for proofs by refutation (Luger 2009, Chapter 14). Suppose we add to the specifications of the previous database a rule for determining whether two people are friends. This may be defined: friends(X, Y) :- likes(X, Z), likes(Y, Z). ” Two issues are important here. pd38 38 5/15/2008 6:34:56 PM Chapter 2 Prolog: Representation 23 because neither the predicate calculus nor Prolog has global variables, the scopes (extent of definition) of X, Y, and Z are limited to the friends rule.

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