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 7
... elements ( 39 ) , each element of which is a nine - element vector . To make a move , do the following : 1. View the vector representing the board as a ternary number . Convert it to a decimal number . 2. Use the number computed in step ...
... elements ( 39 ) , each element of which is a nine - element vector . To make a move , do the following : 1. View the vector representing the board as a ternary number . Convert it to a decimal number . 2. Use the number computed in step ...
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... element's key . Sometimes this key is simply the element itself . This would be done if , for example , the elements being considered were already integers . If the elements are not already in a numeric form , however , they must be ...
... element's key . Sometimes this key is simply the element itself . This would be done if , for example , the elements being considered were already integers . If the elements are not already in a numeric form , however , they must be ...
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... element to the front of a list . It calls itself recursively until all of the elements of L1 have been attached . The LISP function CAR returns the first element of the list it is given and the function CDR returns the list it is given ...
... element to the front of a list . It calls itself recursively until all of the elements of L1 have been attached . The LISP function CAR returns the first element of the list it is given and the function CDR returns the list it is given ...
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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