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
... evaluation functions . A very simple static evaluation function for chess based on 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 ...
... evaluation functions . A very simple static evaluation function for chess based on 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 ...
Página 310
... evaluation function to those positions and simply choose the best one . After doing so , we can back that value up to the starting position to represent our evaluation of it . The starting position is exactly as good for us as the ...
... evaluation function to those positions and simply choose the best one . After doing so , we can back that value up to the starting position to represent our evaluation of it . The starting position is exactly as good for us as the ...
Página 452
... evaluation procedure that combines information from several sources into a single summary statistic . Game - playing programs do this in their static evaluation functions , in which a variety of factors , such as piece advantage and ...
... evaluation procedure that combines information from several sources into a single summary statistic . Game - playing programs do this in their static evaluation functions , in which a variety of factors , such as piece advantage 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