Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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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 287
... situation contain at least two of a script's headers before the script will be activated . Once a script has been activated , there are , as we have already suggested , a variety of ways in which it can be useful in interpreting a ...
... situation contain at least two of a script's headers before the script will be activated . Once a script has been activated , there are , as we have already suggested , a variety of ways in which it can be useful in interpreting a ...
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 ...
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