Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 35
... solve the problem , producing such a specification is itself a very hard problem . Although our ultimate goal is to be able to solve difficult , unstructured problems , such as natural language understanding , it is useful to explore ...
... solve the problem , producing such a specification is itself a very hard problem . Although our ultimate goal is to be able to solve difficult , unstructured problems , such as natural language understanding , it is useful to explore ...
Página 448
... problem solving . The advice may need to be first operationalized , a process explored in Section 17.3 . People also learn through their own problem - solving experience . After solving a complex problem , we remember the structure of the ...
... problem solving . The advice may need to be first operationalized , a process explored in Section 17.3 . People also learn through their own problem - solving experience . After solving a complex problem , we remember the structure of the ...
Página 456
... Problems like choosing which subgoals to tackle and which operators to try ( i.e. , search control problems ) are solved with the same mechanisms as problems in the original problem space . Because the problem solving is uniform ...
... Problems like choosing which subgoals to tackle and which operators to try ( i.e. , search control problems ) are solved with the same mechanisms as problems in the original problem space . Because the problem solving is uniform ...
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