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 311
... choose which successor moves to make and thus which terminal value should be backed up to the next level . Suppose we made move B. Then the opponent must choose among moves E , F , and G. The opponent's goal is to minimize the value of ...
... choose which successor moves to make and thus which terminal value should be backed up to the next level . Suppose we made move B. Then the opponent must choose among moves E , F , and G. The opponent's goal is to minimize the value of ...
Página 321
... choose the optimal move . This assumption is acceptable in winning situations where a move that is guaranteed to be good for us can be found . But , as suggested in Berliner [ 1977 ] , in a losing situation it might be better to take ...
... choose the optimal move . This assumption is acceptable in winning situations where a move that is guaranteed to be good for us can be found . But , as suggested in Berliner [ 1977 ] , in a losing situation it might be better to take ...
Página 438
... choose c , and P should plan accordingly . Given that Q will choose c , P sees that it does better to choose move a than move b . We can now view our discussion of game - playing programs ( Chapter 12 ) from a different perspective ...
... choose c , and P should plan accordingly . Given that Q will choose c , P sees that it does better to choose move a than move b . We can now view our discussion of game - playing programs ( Chapter 12 ) from a different perspective ...
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