Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
Dentro del libro
Resultados 1-3 de 83
Página 310
... choose the best one . After doing so , we can back that value up to the starting position to represent our evaluation of it . The starting position is exactly as good for us as the position generated by the best move we can make next ...
... choose the best one . After doing so , we can back that value up to the starting position to represent our evaluation of it . The starting position is exactly as good for us as the position generated by the best move we can make next ...
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
Weak SlotandFiller Structures | 9 |
6 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
Otras 24 secciones no mostradas
Otras ediciones - Ver todas
Términos y frases comunes
Abbott algorithm answer apply approach Artificial Intelligence assertions attributes axioms backpropagation backtracking backward backward reasoning belief best-first search breadth-first search Cabot Caesar Chapter clauses concept consider constraints contains contexts contradiction corresponding define depth-first depth-first search described discussed domain example explicitly fact given goal graph heuristic heuristic function Horn clauses important inference inheritance input instance interpretation justification knowledge base knowledge representation labeled learning logical assertions Marcus match move MYCIN node nonmonotonic reasoning object operators particular path perceptron possible preconditions predicate logic problem problem-solving procedure produce production system PROLOG propagation propositional logic question represent resolution result robot rules Section semantic semantic net sentence shown in Figure simple slot solution solve space specific statements step strategy structure Suppose suspect syntactic task techniques theorem things tree true truth maintenance system variables wff's