Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas A revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Página 309
... piece advantage was proposed by Turing - simply add the values of black's pieces ( B ) , the values of white's pieces ( W ) , and then compute the quotient W / B . A more sophisticated approach was that taken in Samuel's checkers ...
... piece advantage was proposed by Turing - simply add the values of black's pieces ( B ) , the values of white's pieces ( W ) , and then compute the quotient W / B . A more sophisticated approach was that taken in Samuel's checkers ...
Página 329
... pieces and to solve those pieces separately , to the extent that that is possible . In this chapter , we describe several techniques for doing this in order to construct plans for solving hard problems . 13.1 Overview In Chapter 2 , we ...
... pieces and to solve those pieces separately , to the extent that that is possible . In this chapter , we describe several techniques for doing this in order to construct plans for solving hard problems . 13.1 Overview In Chapter 2 , we ...
Página 473
... piece and position . Next , the explanation is generalized . Using domain knowledge , we find that moving the pieces to a different part of the board is still bad for Black . We can also determine that other pieces besides knights and ...
... piece and position . Next , the explanation is generalized . Using domain knowledge , we find that moving the pieces to a different part of the board is still bad for Black . We can also determine that other pieces besides knights and ...
Contenido
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain example fact function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space