Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 12
... look at several parts of the board at once , whereas the conventional ... seem so great that different strategies seem best . As we learn more about problem ... ahead at the board positions that result from each possible move . Decide ...
... look at several parts of the board at once , whereas the conventional ... seem so great that different strategies seem best . As we learn more about problem ... ahead at the board positions that result from each possible move . Decide ...
Página 13
... look ahead at various sequences of moves in order to find a sequence that leads to a win . It attempts to maximize the likelihood of winning , while assuming that the opponent will try to minimize that likelihood . This algorithm is ...
... look ahead at various sequences of moves in order to find a sequence that leads to a win . It attempts to maximize the likelihood of winning , while assuming that the opponent will try to minimize that likelihood . This algorithm is ...
Página 70
... look ahead from the state it is given to find a solution . It then knows the exact cost of finding that solution and can return that cost as its value . A heuristic function that does this converts the local hill - climbing procedure ...
... look ahead from the state it is given to find a solution . It then knows the exact cost of finding that solution and can return that cost as its value . A heuristic function that does this converts the local hill - climbing procedure ...
Contenido
5 | 24 |
Heuristic Search Techniques | 63 |
Knowledge Representation Issues | 105 |
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 fact frame 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 operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG properties 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