Artificial Intelligence, Volumen1McGraw-Hill, 1983 - 436 páginas What is artificial intelligence?; Problem solving; Problems and problem spaces; Basic problem-solving methods; Game playing; Knowledge representation; Knowledge representation using predicate logic; Knowledge representation using other logics; Structured representation of knowledge; Advanced topics; Advanced problem-solving systems; Natural language understanding; Perception; Learning; Implementing A.lI. systems: languages and machines; Conclusion; References; Index. |
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Página 66
... preconditions of rules match exact board configurations . Thus the matching process is easy but at the price of complete lack of generality in the statement of the rules . As we discussed in Section 2.1 , it is often better to write ...
... preconditions of rules match exact board configurations . Thus the matching process is easy but at the price of complete lack of generality in the statement of the rules . As we discussed in Section 2.1 , it is often better to write ...
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... Preconditions at ( robot , obj ) A small ( obj ) Results at ( obj , loc ) ^ at ( robot , loc ) Preconditions none PICKUP ( obj ) PUTDOWN ( obj ) PLACE ( objl , obj2 ) Results at ( robot , loc ) Preconditions at ( robot , obj ) Results ...
... Preconditions at ( robot , obj ) A small ( obj ) Results at ( obj , loc ) ^ at ( robot , loc ) Preconditions none PICKUP ( obj ) PUTDOWN ( obj ) PLACE ( objl , obj2 ) Results at ( robot , loc ) Preconditions at ( robot , obj ) Results ...
Página 272
... preconditions of lower than peak criticality . Once this is done , use the con- structed plan as the outline of a complete plan , and consider preconditions at the next - lowest criticality level . Augment the plan with operators that ...
... preconditions of lower than peak criticality . Once this is done , use the con- structed plan as the outline of a complete plan , and consider preconditions at the next - lowest criticality level . Augment the plan with operators that ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY backtracking best-first search blocks world branching factor breadth-first search Caesar Chapter chess clauses CLEAR(A complete concept conceptual dependency consider constraint contains database described discussed domain example expert systems exploit explore fact frame game tree given grammar graph heuristic function important input INTERLISP ISA links John knowledge representation labelings learning LISP Marcus match minimax move MTRANS MYCIN node objects ON(B operators parsing particular path performed possible preconditions predicate logic probabilistic problem problem-solving produce production systems PROLOG propositional logic question reasoning representing knowledge resolution rules satisfied script search procedure search process Section semantic net semantic nets sentence shown in Figure simple situation slots solution solve specific statements step strategy structure successors Suppose syntactic task techniques theorem things tion tree true understanding UNSTACK variable variety vertex