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 41
... heuristic . A heuristic is a technique that improves the efficiency of a search process , possibly by sacrificing claims of completeness . Heuristics are like tour guides . They are good to the extent that they point in generally ...
... heuristic . A heuristic is a technique that improves the efficiency of a search process , possibly by sacrificing claims of completeness . Heuristics are like tour guides . They are good to the extent that they point in generally ...
Página 43
... heuristic function that evaluates individual problem states and determines how desirable they are . A heuristic function is a function that maps from problem state descriptions to measures of desirability , usually represented as ...
... heuristic function that evaluates individual problem states and determines how desirable they are . A heuristic function is a function that maps from problem state descriptions to measures of desirability , usually represented as ...
Página 70
... heuristic function now works perfectly . Unfortunately , it is not always possible to construct such a perfect heuristic function . For example , consider again the problem of driving downtown . The perfect heuristic function would need ...
... heuristic function now works perfectly . Unfortunately , it is not always possible to construct such a perfect heuristic function . For example , consider again the problem of driving downtown . The perfect heuristic function would need ...
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