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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... assertions about these functions except that they must exist . So , for example , the formula ⇒y President ( y ) can be transformed into the formula President ( S1 ) where S1 is a function of no arguments that somehow produces a value ...
... assertions about these functions except that they must exist . So , for example , the formula ⇒y President ( y ) can be transformed into the formula President ( S1 ) where S1 is a function of no arguments that somehow produces a value ...
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Elaine Rich. 7.2.4 Scripts Recall that for representing individual assertions , we proposed semantic nets as a useful , general - purpose structure . We then discussed a more special - purpose structure , conceptual dependency , in which ...
Elaine Rich. 7.2.4 Scripts Recall that for representing individual assertions , we proposed semantic nets as a useful , general - purpose structure . We then discussed a more special - purpose structure , conceptual dependency , in which ...
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... Assertions , which simply state known facts . • Theorems , which describe how new facts can be inferred from old ones . A few examples of the kind of knowledge that can be represented as asser- tions in PLANNER are : ( SMELLY GARLIC ) ...
... Assertions , which simply state known facts . • Theorems , which describe how new facts can be inferred from old ones . A few examples of the kind of knowledge that can be represented as asser- tions in PLANNER are : ( SMELLY GARLIC ) ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY Artificial Intelligence backtracking best-first search branching factor breadth-first search Chapter chess clauses CLEAR(A complete Computer concept conceptual dependency consider constraints contains database described discussed domain example expert systems exploit explore fact frame game tree goal grammar graph heuristic heuristic function important input INTERLISP ISA links John knowledge representation labelings learning LISP machine Marcus match methods minimax move MYCIN natural language node objects ON(B operators parsing particular path performed possible preconditions predicate logic probabilistic problem problem-solving produce production system PROLOG propositional logic question reasoning representing knowledge rules Schank script search procedure search process Section semantic net sentence shown in Figure simple situation slots solution solve specific stack statements step strategy structure successors Suppose syntactic task techniques theorem things tion tree true variety