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 308
... game tree will not be able to select even its first move during the lifetime of its opponent . Some kind of heuristic search procedure is necessary . One way of looking at all the search procedures we have discussed is that they are ...
... game tree will not be able to select even its first move during the lifetime of its opponent . Some kind of heuristic search procedure is necessary . One way of looking at all the search procedures we have discussed is that they are ...
Página 320
... game tree to an average depth of six ply and , on the basis of that search , choose a particular move . Although it would have been too expensive to have searched the entire tree to a depth of eight , it is not very expensive to search ...
... game tree to an average depth of six ply and , on the basis of that search , choose a particular move . Although it would have been too expensive to have searched the entire tree to a depth of eight , it is not very expensive to search ...
Página 322
... game - playing programs , however . It seems that game trees containing won positions and nonrandom distributions of heuristic estimates provide environments that are conducive to minimaxing . 12.5 Iterative Deepening A number of ideas ...
... game - playing programs , however . It seems that game trees containing won positions and nonrandom distributions of heuristic estimates provide environments that are conducive to minimaxing . 12.5 Iterative Deepening A number of ideas ...
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