Artificial Intelligence, Volumen1McGraw-Hill, 1983 - 436 páginas What is artificial intelligence?; Problem solving; Problems and problem spaces; Basic problem-solving methods; Game playing; Knowledge representation; Knowledge representation using predicate logic; Knowledge representation using other logics; Structured representation of knowledge; Advanced topics; Advanced problem-solving systems; Natural language understanding; Perception; Learning; Implementing A.lI. systems: languages and machines; Conclusion; References; Index. |
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Página 115
... evaluation function , which uses whatever information it has to evaluate individual board positions by es- timating how likely they are to lead eventually to a win . Its function is similar to that of the heuristic function h ' in the A ...
... evaluation function , which uses whatever information it has to evaluate individual board positions by es- timating how likely they are to lead eventually to a win . Its function is similar to that of the heuristic function h ' in the A ...
Página 116
... evaluation function . Both of these must incorporate a great deal of knowledge about the particular game being played . But unless these functions are perfect , we also need a search procedure that makes it possible to look ahead as ...
... evaluation function . Both of these must incorporate a great deal of knowledge about the particular game being played . But unless these functions are perfect , we also need a search procedure that makes it possible to look ahead as ...
Página 117
... evaluation function that returns values ranging from 10 to 10 , with 10 indicat- ing a win for us , -10 a win for the opponent , and O an even match . Since our goal is to maximize the value of the heuristic function , we choose to move ...
... evaluation function that returns values ranging from 10 to 10 , with 10 indicat- ing a win for us , -10 a win for the opponent , and O an even match . Since our goal is to maximize the value of the heuristic function , we choose to move ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY backtracking best-first search blocks world branching factor breadth-first search Caesar Chapter chess clauses CLEAR(A complete concept conceptual dependency consider constraint contains database described discussed domain example expert systems exploit explore fact frame game tree given grammar graph heuristic function important input INTERLISP ISA links John knowledge representation labelings learning LISP Marcus match minimax move MTRANS MYCIN node objects ON(B operators parsing particular path performed possible preconditions predicate logic probabilistic problem problem-solving produce production systems PROLOG propositional logic question reasoning representing knowledge resolution rules satisfied script search procedure search process Section semantic net semantic nets sentence shown in Figure simple situation slots solution solve specific statements step strategy structure successors Suppose syntactic task techniques theorem things tion tree true understanding UNSTACK variable variety vertex