Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 35
... possible to automate this process , it must be done by hand , however . For simple problems , such as chess or the ... possible configurations of the relevant objects ( and perhaps some impossible ones ) . It is , of course , possible to ...
... possible to automate this process , it must be done by hand , however . For simple problems , such as chess or the ... possible configurations of the relevant objects ( and perhaps some impossible ones ) . It is , of course , possible to ...
Página 373
... possible for it . Then we move to an adjacent vertex and find all of its possible labelings . The line that we followed to get from the first vertex to the second must end up with only one label , and that label must be consistent with ...
... possible for it . Then we move to an adjacent vertex and find all of its possible labelings . The line that we followed to get from the first vertex to the second must end up with only one label , and that label must be consistent with ...
Página 435
... possible for each agent to build a model of both itself and the other agents with which it must interact . The self - descriptive model is necessary to enable the agent to know when it should get help from others and to allow it to ...
... possible for each agent to build a model of both itself and the other agents with which it must interact . The self - descriptive model is necessary to enable the agent to know when it should get help from others and to allow it to ...
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