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 126
... situation . But , of course , that situation may change . Then information about what happened ( for example , we walked around the room we were looking at ) may be useful in selecting a new structure to describe the revised situation ...
... situation . But , of course , that situation may change . Then information about what happened ( for example , we walked around the room we were looking at ) may be useful in selecting a new structure to describe the revised situation ...
Página 321
... 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 the risk that the opponent will make a mistake . Suppose we must ...
... 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 the risk that the opponent will make a mistake . Suppose we must ...
Página 530
... situation ( b ) , the ball will travel upward and to the right , then downward . In situation ( c ) , the ball will swing repeatedly from left to right , finally coming to rest in the middle . Now , how can we build a computer program ...
... situation ( b ) , the ball will travel upward and to the right , then downward . In situation ( c ) , the ball will swing repeatedly from left to right , finally coming to rest in the middle . Now , how can we build a computer program ...
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