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 82
... choose as our next node to expand the node that appears to be closest to the goal . This is useful if we care about ... choosing the node that seems closest to a goal If we want to find a path involving the fewest number of steps , then ...
... choose as our next node to expand the node that appears to be closest to the goal . This is useful if we care about ... choosing the node that seems closest to a goal If we want to find a path involving the fewest number of steps , then ...
Página 118
... choose which of the successor moves will be made and thus which terminal value should be backed up to the next level . Suppose we made move B. Then the opponent must choose among moves E , F , and G. The opponent's goal is to minimize ...
... choose which of the successor moves will be made and thus which terminal value should be backed up to the next level . Suppose we made move B. Then the opponent must choose among moves E , F , and G. The opponent's goal is to minimize ...
Página 129
... choose the optimal move . This as- sumption is acceptable in winning situations in which a move that is guaranteed to be good for us can be found . But , as suggested in [ Berliner , 1977 ] , in a losing situation it might be better to ...
... choose the optimal move . This as- sumption is acceptable in winning situations in which a move that is guaranteed to be good for us can be found . But , as suggested in [ Berliner , 1977 ] , in a losing situation it might be better to ...
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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 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