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 42
... leads to the discovery of squaring iff is the multiplication function , and it leads to the discovery of an identity function if ƒ is the function of set union . In less formal domains , this same heuristic leads to the discovery of ...
... leads to the discovery of squaring iff is the multiplication function , and it leads to the discovery of an identity function if ƒ is the function of set union . In less formal domains , this same heuristic leads to the discovery of ...
Página 321
... lead to situations that are very bad for us , but one is slightly less bad than the other . But further suppose that the less promising move could lead to a very good situation for us if the opponent makes a single mistake . Although ...
... lead to situations that are very bad for us , but one is slightly less bad than the other . But further suppose that the less promising move could lead to a very good situation for us if the opponent makes a single mistake . Although ...
Página 338
... lead to a solution ( or at least appears unlikely to lead to one ) . The same reasoning mechanisms that can be used to detect a solution can often be used for detecting a dead end . If the search process is reasoning forward from the ...
... lead to a solution ( or at least appears unlikely to lead to one ) . The same reasoning mechanisms that can be used to detect a solution can often be used for detecting a dead end . If the search process is reasoning forward from 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