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 239
... section , we described CF's as a mechanism for reducing the complexity of a Bayesian reasoning system by making some approximations to the formalism . In this section , we describe an alternative approach , Bayesian networks [ Pearl ...
... section , we described CF's as a mechanism for reducing the complexity of a Bayesian reasoning system by making some approximations to the formalism . In this section , we describe an alternative approach , Bayesian networks [ Pearl ...
Página 301
... section we briefly discuss three additional methods : constraints , simulation models , and subsymbolic systems . Keep in mind throughout this discussion that it is not always the case that these various representational systems are ...
... section we briefly discuss three additional methods : constraints , simulation models , and subsymbolic systems . Keep in mind throughout this discussion that it is not always the case that these various representational systems are ...
Página 410
... Section 15.3 ) . In the rest of this section , we discuss the second . Montague Semantics Recall that we argued in Section 15.1.1 that the reason syntactic parsing was a good idea was that it produces structures that correspond to the ...
... Section 15.3 ) . In the rest of this section , we discuss the second . Montague Semantics Recall that we argued in Section 15.1.1 that the reason syntactic parsing was a good idea was that it produces structures that correspond to the ...
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