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 23
... stored , with each stimulus image , a cue that it could later pass through the discrimination net to try to find the correct response image . But it stored as a cue only as much information about the response syllable as was necessary ...
... stored , with each stimulus image , a cue that it could later pass through the discrimination net to try to find the correct response image . But it stored as a cue only as much information about the response syllable as was necessary ...
Página 112
... stored explicitly for Three Finger Brown , we follow the instance attribute to Pitcher and extract the value stored there . Now we observe one of the critical characteristics of property inheritance , namely that it may produce default ...
... stored explicitly for Three Finger Brown , we follow the instance attribute to Pitcher and extract the value stored there . Now we observe one of the critical characteristics of property inheritance , namely that it may produce default ...
Página 450
... stored value than it would be to recompute it , there must be a way to access the appropriate stored value quickly . In Samuel's program , this was done by indexing board positions by a few important characteristics , such as the number ...
... stored value than it would be to recompute it , there must be a way to access the appropriate stored value quickly . In Samuel's program , this was done by indexing board positions by a few important characteristics , such as the number ...
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