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 233
... Bayesian networks • Dempster - Shafer theory We also mention one very different numerical approach to uncertainty , fuzzy logic . There has been an active , strident debate for many years on the question of whether pure Bayesian ...
... Bayesian networks • Dempster - Shafer theory We also mention one very different numerical approach to uncertainty , fuzzy logic . There has been an active , strident debate for many years on the question of whether pure Bayesian ...
Página 237
... Bayesian statistics . We argued at the end of the last section that pure Bayesian statistics usually leads to intractable systems . But MYCIN works [ Buchanan and Shortliffe , 1984 ] . Why ? Each CF in a MYCIN rule represents the ...
... Bayesian statistics . We argued at the end of the last section that pure Bayesian statistics usually leads to intractable systems . But MYCIN works [ Buchanan and Shortliffe , 1984 ] . Why ? Each CF in a MYCIN rule represents the ...
Página 239
... Bayesian networks in the next section , we describe a systematic solution to this problem . We can summarize this discussion of certainty factors and rule - based systems as follows . The approach ... BAYESIAN NETWORKS 239 Bayesian Networks.
... Bayesian networks in the next section , we describe a systematic solution to this problem . We can summarize this discussion of certainty factors and rule - based systems as follows . The approach ... BAYESIAN NETWORKS 239 Bayesian Networks.
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