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 145
... considered . Conjunctive normal form [ Davis and Putnam , 1960 ] has both of these properties . For example , the formula given above for the feelings of Romans who know Marcus would be represented in conjunctive normal form as Roman ...
... considered . Conjunctive normal form [ Davis and Putnam , 1960 ] has both of these properties . For example , the formula given above for the feelings of Romans who know Marcus would be represented in conjunctive normal form as Roman ...
Página 207
... considered the statement A ( Joe ) V B ( Joe ) . • It assumes that all predicates have all of their instances listed . Although in many database applications this is true , in many knowledge - based systems it is not . Some predicates ...
... considered the statement A ( Joe ) V B ( Joe ) . • It assumes that all predicates have all of their instances listed . Although in many database applications this is true , in many knowledge - based systems it is not . Some predicates ...
Página 243
... considered because they have no significance in the problem domain ( and so their associated value of m will be 0 ) . Let's see how m works for our diagnosis problem . Assume that we have no infor- mation about how to choose among the ...
... considered because they have no significance in the problem domain ( and so their associated value of m will be 0 ) . Let's see how m works for our diagnosis problem . Assume that we have no infor- mation about how to choose among 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