Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 31
... space representation seems natural for chess because the set of states , which corresponds to the set of board positions , is artificial and well - organized . This same kind of representation is also useful for naturally occurring ...
... space representation seems natural for chess because the set of states , which corresponds to the set of board positions , is artificial and well - organized . This same kind of representation is also useful for naturally occurring ...
Página 469
... space requirements of the exhaustive , breadth- first search mentioned above . Another is that inconsistent data , also called noise , can cause the candidate elimination algorithm to prune the target concept from the version space ...
... space requirements of the exhaustive , breadth- first search mentioned above . Another is that inconsistent data , also called noise , can cause the candidate elimination algorithm to prune the target concept from the version space ...
Página 571
... space , known as configuration space , or c - space [ Lozano - Perez et al . , 1984 ] . If we want to allow rotations , we can represent the robot as a combination of point P and some angle of rotation 0. The robot can now be considered ...
... space , known as configuration space , or c - space [ Lozano - Perez et al . , 1984 ] . If we want to allow rotations , we can represent the robot as a combination of point P and some angle of rotation 0. The robot can now be considered ...
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