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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... result of appending SUCC to PATH ( RESULT - SUCC ) . 7. Now that all the successors have been examined , we know what the value of NODE is , as well as what path to take from it . So return the structure VALUE = PATH BEST - SCORE ...
... result of appending SUCC to PATH ( RESULT - SUCC ) . 7. Now that all the successors have been examined , we know what the value of NODE is , as well as what path to take from it . So return the structure VALUE = PATH BEST - SCORE ...
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... result of appending SUCC to PATH ( RESULT - SUCC ) . 4. If PASS - THRESH ( reflecting the current best value ) is not better than USE - THRESH , then we should stop examining this branch . But both thresholds and values have been ...
... result of appending SUCC to PATH ( RESULT - SUCC ) . 4. If PASS - THRESH ( reflecting the current best value ) is not better than USE - THRESH , then we should stop examining this branch . But both thresholds and values have been ...
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... result of appending [ XIL1 ] to L2 is [ X / L3 ] provided that it can be shown that the result of appending L1 to L2 is L3 . Example 2 Compute the Discriminant of a Quadratic Equation - discrim ( A , B , C , D ) : - mult ( B , B ...
... result of appending [ XIL1 ] to L2 is [ X / L3 ] provided that it can be shown that the result of appending L1 to L2 is L3 . Example 2 Compute the Discriminant of a Quadratic Equation - discrim ( A , B , C , D ) : - mult ( B , B ...
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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