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 158
... Given that that standardization has been done , it is easy to determine how the unifier must be used to perform substitutions to create the resolvent . If two instances of the same variable occur , then they must be given identical ...
... Given that that standardization has been done , it is easy to determine how the unifier must be used to perform substitutions to create the resolvent . If two instances of the same variable occur , then they must be given identical ...
Página 186
... given some set of observations we have made . Let = P ( H ; | E ) P ( E / H1 ) = P ( H ; ) = k = the probability that hypothesis H ; is true given evidence E the probability that we will observe evidence E given that hypothesis i is ...
... given some set of observations we have made . Let = P ( H ; | E ) P ( E / H1 ) = P ( H ; ) = k = the probability that hypothesis H ; is true given evidence E the probability that we will observe evidence E given that hypothesis i is ...
Página 194
... given as CF [ h , e ] = MB [ h , e ] - MD [ h , e ] Notice that if CF is positive , the system believes that the hypothesis is true ; if CF is negative , there is more evidence against it and the system believes it to be false . By ...
... given as CF [ h , e ] = MB [ h , e ] - MD [ h , e ] Notice that if CF is positive , the system believes that the hypothesis is true ; if CF is negative , there is more evidence against it and the system believes it to be false . By ...
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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