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 40
... explored until all shorter ones have already been examined . This contrasts with depth - first search , which may ... explore all possible paths in the tree and return the one with the shortest length . This approach will even work in ...
... explored until all shorter ones have already been examined . This contrasts with depth - first search , which may ... explore all possible paths in the tree and return the one with the shortest length . This approach will even work in ...
Página 315
... explore any of the other branches of G. From this example , we see that at maximizing levels , we can rule out a move early if it becomes clear that its value will be less than the current threshold , while at minimizing levels , search ...
... explore any of the other branches of G. From this example , we see that at maximizing levels , we can rule out a move early if it becomes clear that its value will be less than the current threshold , while at minimizing levels , search ...
Página 388
... explored to find one that meets all the constraints imposed by a particular sentence . As for any search process , we must decide whether to explore all possible paths or , instead , to explore only a single most likely one and to ...
... explored to find one that meets all the constraints imposed by a particular sentence . As for any search process , we must decide whether to explore all possible paths or , instead , to explore only a single most likely one and to ...
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