Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 77
... propagate down to a node , see if its parent points to the node we are coming from . If so , continue the propagation . If not , then its g value already reflects the better path of which it is part . So the propagation may stop here ...
... propagate down to a node , see if its parent points to the node we are coming from . If so , continue the propagation . If not , then its g value already reflects the better path of which it is part . So the propagation may stop here ...
Página 89
... Propagation can then occur with this new constraint , and so forth . The first step , propagation , arises from the fact that there are usually dependencies among the constraints . These dependencies occur because many constraints ...
... Propagation can then occur with this new constraint , and so forth . The first step , propagation , arises from the fact that there are usually dependencies among the constraints . These dependencies occur because many constraints ...
Página 90
... propagation terminates for one of two reasons . First , a contradiction may be detected . If this happens , then there is no solution consistent with all the known constraints . If the contradiction involves only those constraints that ...
... propagation terminates for one of two reasons . First , a contradiction may be detected . If this happens , then there is no solution consistent with all the known constraints . If the contradiction involves only those constraints that ...
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