By George F. Luger, William A Stubblefield
AI Algorithms, facts buildings, and Idioms in Prolog, Lisp, and Java
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Additional resources for AI algorithms, data structures, and idioms in Prolog, Lisp, and Java
Thus: likes(X, susie). or, better, likes(Everyone, susie). , when a variable is used in a predicate it is understood that it is true for all the domain elements within its scope. 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)).
Hint: several meta-predicates such as atom() can be helpful. 5. Implement a frame system with inheritance that supports the definition of three kinds of slots: properties of a class that may be inherited by subclasses, properties that are inherited by instances of the class but not by subclasses, and properties of the class and its subclasses that are not inherited by instances (class properties). Discuss the benefits, uses, and problems with this distinction. 3 Abstract Data Types in Prolog Introduction We next introduce the 3 x 3 knight’s tour problem, create a predicate calculus based representation of problem states, and a recursive search of its state space.
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. The predicate names (likes), the number or order of parameters, and even whether a given predicate always has the same number of parameters are determined by the design requirements (the implicit “semantics”) of the problem.