Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 13
Elaine Rich. 2. Otherwise , consider all the moves the opponent could make next . See which of them is worst for us ( by recursively calling this procedure ) . Assume the opponent will make that move . Whatever rating that move has ...
Elaine Rich. 2. Otherwise , consider all the moves the opponent could make next . See which of them is worst for us ( by recursively calling this procedure ) . Assume the opponent will make that move . Whatever rating that move has ...
Página 311
... opponent gets to 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 ...
... opponent gets to 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 ...
Página 321
... opponent will make a mistake . Suppose we must choose between two moves , both of which , if the opponent plays perfectly , lead to situations that are very bad for us , but one is slightly less bad than the other . But further suppose ...
... opponent will make a mistake . Suppose we must choose between two moves , both of which , if the opponent plays perfectly , lead to situations that are very bad for us , but one is slightly less bad than the other . But further suppose ...
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