Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 46
... ON ( B , C ) and ON ( A , B ) ON ( B , C ) Put B on C ON ( B , C ) ON ( A , B ) CLEAR ( A ) ON ( A , B ) Move A to table Put A on B ON ( A , B ) CLEAR ( A ) Figure 2.11 : A Proposed Solution for the Blocks Problem 1. CLEAR ( x ) [ block ...
... ON ( B , C ) and ON ( A , B ) ON ( B , C ) Put B on C ON ( B , C ) ON ( A , B ) CLEAR ( A ) ON ( A , B ) Move A to table Put A on B ON ( A , B ) CLEAR ( A ) Figure 2.11 : A Proposed Solution for the Blocks Problem 1. CLEAR ( x ) [ block ...
Página 342
... ON ( B , A ) , to the world model , we see that it is satisfied . So we pop it off and consider the next goal ... ON ( B , D ) ON ( C , A ) ^ ON ( B , D ) ^ OTAD We now attempt to satisfy the goal HOLDING ( C ) . There are two operators ...
... ON ( B , A ) , to the world model , we see that it is satisfied . So we pop it off and consider the next goal ... ON ( B , D ) ON ( C , A ) ^ ON ( B , D ) ^ OTAD We now attempt to satisfy the goal HOLDING ( C ) . There are two operators ...
Página 346
... from B. By the time we have achieved the goal ON ( B , C ) and popped it off the stack , we will have executed the following additional sequence of operators : UNSTACK ( A , B ) PUTDOWN ( A ) 5 . 6 . 7. PICKUP ( B ) 8 . STACK ( B , C ) ...
... from B. By the time we have achieved the goal ON ( B , C ) and popped it off the stack , we will have executed the following additional sequence of operators : UNSTACK ( A , B ) PUTDOWN ( A ) 5 . 6 . 7. PICKUP ( B ) 8 . STACK ( B , C ) ...
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