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 67
... match first . Sometimes a great many values satisfy each predicate but very few satisfy both . This example also ... Matching A more complex matching process SEC . 3.4 MATCHING 67.
... match first . Sometimes a great many values satisfy each predicate but very few satisfy both . This example also ... Matching A more complex matching process SEC . 3.4 MATCHING 67.
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... matching rules are simple . Different constants , functions , or predicates cannot match ; identical ones can . A variable can match ' another variable , any constant , or a function or predicate expression , with the restriction that ...
... matching rules are simple . Different constants , functions , or predicates cannot match ; identical ones can . A variable can match ' another variable , any constant , or a function or predicate expression , with the restriction that ...
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... match to update the current vista , the set of spaces currently in focus , so that the next match can proceed efficiently . Continuing with our example , we see that when the first sentence is under- stood , space S2 becomes in focus ...
... match to update the current vista , the set of spaces currently in focus , so that the next match can proceed efficiently . Continuing with our example , we see that when the first sentence is under- stood , space S2 becomes in focus ...
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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