Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 389
... interpretation of the sentence . In this example , if the auxiliary verb interpretation of " have " were chosen first and the end of the sentence appeared with no main verb having been seen , the understander would detect failure and ...
... interpretation of the sentence . In this example , if the auxiliary verb interpretation of " have " were chosen first and the end of the sentence appeared with no main verb having been seen , the understander would detect failure and ...
Página 400
... interpretation , which is usually used to set up strong expectations for particular sentence structures . • Approximately compositional semantic interpretation , in which semantic pro- cessing is applied to the result of performing a ...
... interpretation , which is usually used to set up strong expectations for particular sentence structures . • Approximately compositional semantic interpretation , in which semantic pro- cessing is applied to the result of performing a ...
Página 408
... interpretation is chosen and the process terminates . If , however , the sentence had been John went to the park with the fountain . the process would not have stopped since a fountain is inanimate and cannot move . Then the third ...
... interpretation is chosen and the process terminates . If , however , the sentence had been John went to the park with the fountain . the process would not have stopped since a fountain is inanimate and cannot move . Then the third ...
Contenido
5 | 24 |
Heuristic Search Techniques | 63 |
Knowledge Representation Issues | 105 |
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 fact frame 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 operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG properties 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