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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... Bill , using the net John Bill Height Height Greater - than H1 H2 The nodes H1 and H2 represent the new concepts JOHN'S - HEIGHT and BILL'S - HEIGHT , respectively . They are defined by their relationships to the nodes JOHN and BILL ...
... Bill , using the net John Bill Height Height Greater - than H1 H2 The nodes H1 and H2 represent the new concepts JOHN'S - HEIGHT and BILL'S - HEIGHT , respectively . They are defined by their relationships to the nodes JOHN and BILL ...
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Elaine Rich. Bill A Mary Mary Bill Bill MTRANS Bill ↑ PTRANS speak To To Bill Ʌ Mary words happiness = -10 Mary Movies Bill Mary Figure 9-1 : The Conceptual Dependency Representation of a Paragraph A : = B + C + D Although one - to ...
Elaine Rich. Bill A Mary Mary Bill Bill MTRANS Bill ↑ PTRANS speak To To Bill Ʌ Mary words happiness = -10 Mary Movies Bill Mary Figure 9-1 : The Conceptual Dependency Representation of a Paragraph A : = B + C + D Although one - to ...
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... Bill S VP PP hit Bill was hit Mary hit Bill . by Bill was hit by Mary . Figure 9-12 : Syntactic Parses of an Active and a Passive Sentence Mary Although the semantic roles of Mary and Bill are identical in these two sentences , their ...
... Bill S VP PP hit Bill was hit Mary hit Bill . by Bill was hit by Mary . Figure 9-12 : Syntactic Parses of an Active and a Passive Sentence Mary Although the semantic roles of Mary and Bill are identical in these two sentences , their ...
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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