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 125
... intersection of those sets to get the structure ( s ) , preferably precisely one , that involves all the content words . Given the pointers just described and the story about John's trip to Steak and Ale , the restaurant script would be ...
... intersection of those sets to get the structure ( s ) , preferably precisely one , that involves all the content words . Given the pointers just described and the story about John's trip to Steak and Ale , the restaurant script would be ...
Página 252
... Intersection Search One of the early ways that semantic nets were used was to find relationships among objects by spreading activation out from each of two nodes and seeing where the activation met . This process is called intersection ...
... Intersection Search One of the early ways that semantic nets were used was to find relationships among objects by spreading activation out from each of two nodes and seeing where the activation met . This process is called intersection ...
Página 371
... intersection of the planes corresponding to the faces of vertex A. Imagine viewing this figure from each of the remaining seven octants and recording the configuration and the labeling of vertex A. Figure 14.16 ( a ) shows the results ...
... intersection of the planes corresponding to the faces of vertex A. Imagine viewing this figure from each of the remaining seven octants and recording the configuration and the labeling of vertex A. Figure 14.16 ( a ) shows the results ...
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