Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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... script is instantiated for this text , and because of the last sentence , the path through step 14 of the script is the one that is used in forming the representation of this text . When the script is instantiated M ' is bound to the ...
... script is instantiated for this text , and because of the last sentence , the path through step 14 of the script is the one that is used in forming the representation of this text . When the script is instantiated M ' is bound to the ...
Página 285
Elaine Rich. Figure 10.5 shows part of a typical script , the restaurant script ( taken from Schank and Abelson ... Script : RESTAURANT Track : Coffee Shop Props : Tables 10.2 . SCRIPTS 285.
Elaine Rich. Figure 10.5 shows part of a typical script , the restaurant script ( taken from Schank and Abelson ... Script : RESTAURANT Track : Coffee Shop Props : Tables 10.2 . SCRIPTS 285.
Página 287
... script should be activated . In order to cut down on the number of times a spurious script is activated , it has proved useful to require that a situation contain at least two of a script's headers before the script will be activated ...
... script should be activated . In order to cut down on the number of times a spurious script is activated , it has proved useful to require that a situation contain at least two of a script's headers before the script will be activated ...
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