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 59
... theorems to axioms . This suggests that it would be much better to reason back- ward when trying to prove theorems . Mathematicians have long realized this [ Polya , 1957 ] , as have the designers of theorem - proving programs . One of ...
... theorems to axioms . This suggests that it would be much better to reason back- ward when trying to prove theorems . Mathematicians have long realized this [ Polya , 1957 ] , as have the designers of theorem - proving programs . One of ...
Página 167
... theorem proving that corresponds more closely to the processes used in human theorem proving . We are thus led to what we call , mostly by definition , natural deduction . Natural deduction is not a precise term . Rather it describes a ...
... theorem proving that corresponds more closely to the processes used in human theorem proving . We are thus led to what we call , mostly by definition , natural deduction . Natural deduction is not a precise term . Rather it describes a ...
Página 396
... theorems , that describe backward or goal - directed reasoning . An example of a consequent theorem is [ CONSEQUENT ( PART $ ? X $ ? Z ) ( GOAL ( PART $ ? X $ ? Y ) ) ( GOAL ( PART $ ? Y $ ? Z ) ) ] This theorem says that if you want to ...
... theorems , that describe backward or goal - directed reasoning . An example of a consequent theorem is [ CONSEQUENT ( PART $ ? X $ ? Z ) ( GOAL ( PART $ ? X $ ? Y ) ) ( GOAL ( PART $ ? Y $ ? Z ) ) ] This theorem says that if you want to ...
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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