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 85
... interaction between subgoals . A simple example of this failure is shown in Figure 3.10 . Assuming that both node C and node E ultimately lead to ... interactions among subgoals are presented . B A A D B C D G H E 3.4 . PROBLEM REDUCTION 85.
... interaction between subgoals . A simple example of this failure is shown in Figure 3.10 . Assuming that both node C and node E ultimately lead to ... interactions among subgoals are presented . B A A D B C D G H E 3.4 . PROBLEM REDUCTION 85.
Página 330
... interactions among subproblems and to handle them appropriately . Several methods for doing these two kinds of decomposition have been proposed and we investigate them in this chapter . These methods focus on ways of decomposing the ...
... interactions among subproblems and to handle them appropriately . Several methods for doing these two kinds of decomposition have been proposed and we investigate them in this chapter . These methods focus on ways of decomposing the ...
Página 364
... interactions increases , so does the complexity of the mapping . Programming languages provide good examples of languages in which there is very little interaction among the components of an input . For example , Figure 14.4 shows how ...
... interactions increases , so does the complexity of the mapping . Programming languages provide good examples of languages in which there is very little interaction among the components of an input . For example , Figure 14.4 shows how ...
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