Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas A revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Página 70
... method by embedding a global method within it . But now the computational advantages of a local method have been lost . Thus it is still true that hill climbing can be very inefficient in a large , rough problem space . But it is often ...
... method by embedding a global method within it . But now the computational advantages of a local method have been lost . Thus it is still true that hill climbing can be very inefficient in a large , rough problem space . But it is often ...
Página 241
... method [ Pearl , 1988 ] , a clique triangulation method [ Lauritzen and Spiegelhal- ter , 1988 ] , and a variety of stochastic algorithms . The idea behind these methods is to take advantage of the fact that nodes have limited domains ...
... method [ Pearl , 1988 ] , a clique triangulation method [ Lauritzen and Spiegelhal- ter , 1988 ] , and a variety of stochastic algorithms . The idea behind these methods is to take advantage of the fact that nodes have limited domains ...
Página 480
... method for transforming old solutions into new solutions . Whole solutions are viewed as states in a problem space called T - space . T- operators prescribe the methods of transforming solutions ( states ) into other solutions ...
... method for transforming old solutions into new solutions . Whole solutions are viewed as states in a problem space called T - space . T- operators prescribe the methods of transforming solutions ( states ) into other solutions ...
Contenido
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain example fact function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space