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 10
... opponent's win . Posswin operates by checking , one at a time , each of the rows , columns , and diagonals . Because of the way values are numbered , it can test an entire row ( column or diagonal ) to see if it is a possible win by ...
... opponent's win . Posswin operates by checking , one at a time , each of the rows , columns , and diagonals . Because of the way values are numbered , it can test an entire row ( column or diagonal ) to see if it is a possible win by ...
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 always choose the optimal move . This assumption is acceptable in winning situations where a move that is ... opponent's playing style so that the likelihood of various mistakes can be estimated . But this is very hard to ...
... opponent will always choose the optimal move . This assumption is acceptable in winning situations where a move that is ... opponent's playing style so that the likelihood of various mistakes can be estimated . But this is very hard to ...
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