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 199
... present several logical formalisms that provide mechanisms for performing nonmonotonic reasoning . In the last four , we discuss approaches to the implementation of such reasoning in problem - solving programs . For more detailed ...
... present several logical formalisms that provide mechanisms for performing nonmonotonic reasoning . In the last four , we discuss approaches to the implementation of such reasoning in problem - solving programs . For more detailed ...
Página 232
... present then certain physical characteristics will be observed , then we can use Bayes ' formula to compute , from the evidence we collect , how likely it is that the various minerals are present . This is , in fact , what is done by ...
... present then certain physical characteristics will be observed , then we can use Bayes ' formula to compute , from the evidence we collect , how likely it is that the various minerals are present . This is , in fact , what is done by ...
Página 397
... present ( at the top level ) in either G1 or G2 do i . If A is not present at the top level in the other input , then add A and its value to NEW . ii . If it is , then call Graph - Unify with the two values for A. If that fails , then ...
... present ( at the top level ) in either G1 or G2 do i . If A is not present at the top level in the other input , then add A and its value to NEW . ii . If it is , then call Graph - Unify with the two values for A. If that fails , then ...
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