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 80
... selecting at each cycle the most interesting task , doing it , and possibly generating new tasks in the process . This corresponds to the selection of the most promising node in the best - first search procedure . But in AM's situation ...
... selecting at each cycle the most interesting task , doing it , and possibly generating new tasks in the process . This corresponds to the selection of the most promising node in the best - first search procedure . But in AM's situation ...
Página 124
... selection of the most appropriate structure . • How to fill in appropriate details from the current situation ... Selecting an Initial Structure Selecting candidate knowledge structures to match a particular problem - solving situation ...
... selection of the most appropriate structure . • How to fill in appropriate details from the current situation ... Selecting an Initial Structure Selecting candidate knowledge structures to match a particular problem - solving situation ...
Página 125
... selecting simple structures , such as those representing the meanings of individual words , though , this approach may ... selection or to make a completely new one if necessary . For a discussion of this approach , see Charniak [ 1978 ] ...
... selecting simple structures , such as those representing the meanings of individual words , though , this approach may ... selection or to make a completely new one if necessary . For a discussion of this approach , see Charniak [ 1978 ] ...
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