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 71
... function is a function that maps from problem state descriptions to measures of desirability , usually represented as numbers . Which aspects of the problem state are considered , how those aspects are evaluated , and the weights given ...
... function is a function that maps from problem state descriptions to measures of desirability , usually represented as numbers . Which aspects of the problem state are considered , how those aspects are evaluated , and the weights given ...
Página 72
... Functions salesman ) . It does not matter , in general , which way the function is stated . The program that uses the values of the function can attempt to minimize it or to maximize it as appropriate . The purpose of a heuristic function ...
... Functions salesman ) . It does not matter , in general , which way the function is stated . The program that uses the values of the function can attempt to minimize it or to maximize it as appropriate . The purpose of a heuristic function ...
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... 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 ...
... 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 ...
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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