By George F. Luger, William A Stubblefield
AI Algorithms, facts constructions, 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
Continued prompts force Prolog to find all possible solutions to the query. When no further solutions exist, the interpreter responds no. This example also illustrates the closed world assumption or negation as failure. ” For the query likes(george, beer), the interpreter looks for the predicate likes(george, beer) or some rule that could establish likes(george, beer). Failing this, the request is false. Prolog assumes that all knowledge of the world is present in the database. The closed world assumption introduces a number of practical and philosophical difficulties in the language.
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. ” There are many reasons supporting this restricted form, most important is the power and computational efficiency of a resolution refutation system. For details see Luger (2009, Chapter 14). A Simple Prolog Program A Prolog program is a set of specifications in the first-order predicate calculus describing the objects and relations in a problem domain.
This product was built using the “C” language on the DEC-system 10 and could operate in both interpretive and compiled modes (Warren, Pereira, et al. 1979). Further descriptions of this early code and comparisons of Prolog with Lisp may be found in Warren et al. (Warren, Pereira, et al. 1977). This “Warren and Pereira” Prolog became the early standard. The book Programming in Prolog (Clocksin and Mellish 1984, now in its fifth edition) was created by two other researchers at the Department of Artificial Intelligence, Bill Clocksin and Chris Mellish.