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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... ends of the links would be the values . The net shown in Figure 7-3 would be represented in LISP as shown in Figure 7-4 . ATOM CHAIR MY - CHAIR PROPERTY LIST ( ( ISA SEC . 7.2 DECLARATIVE REPRESENTATIONS 215 Semantic Nets.
... ends of the links would be the values . The net shown in Figure 7-3 would be represented in LISP as shown in Figure 7-4 . ATOM CHAIR MY - CHAIR PROPERTY LIST ( ( ISA SEC . 7.2 DECLARATIVE REPRESENTATIONS 215 Semantic Nets.
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... semantic nets lies in the ability of programs to manipulate them to solve problems . One of the early ways that semantic nets were used was to find relationships among objects by spreading activation out from each of two nodes and ...
... semantic nets lies in the ability of programs to manipulate them to solve problems . One of the early ways that semantic nets were used was to find relationships among objects by spreading activation out from each of two nodes and ...
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... Semantic Spectrum of Representation At this point , it is useful to review ... nets • Frames • Conceptual dependency • Scripts Of these , predicate logic ... Semantic nets , as their name implies , are more semantically oriented . They ...
... Semantic Spectrum of Representation At this point , it is useful to review ... nets • Frames • Conceptual dependency • Scripts Of these , predicate logic ... Semantic nets , as their name implies , are more semantically oriented . They ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY Artificial Intelligence backtracking best-first search blocks world branching factor breadth-first search Caesar Chapter chess clauses CLEAR(A complete concept conceptual dependency consider constraints contains database described discussed domain example exploit explore fact frame game tree goal grammar graph heuristic heuristic function important input INTERLISP ISA links John knowledge representation labelings LISP Marcus match methods minimax move MYCIN natural language necessary 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 understanding variety