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 12
... look at several parts of the board at once , whereas the conventional computer must look at the squares one at a time . Sometimes an investigation of how people solve problems sheds great light on how computers should do so . At other ...
... look at several parts of the board at once , whereas the conventional computer must look at the squares one at a time . Sometimes an investigation of how people solve problems sheds great light on how computers should do so . At other ...
Página 73
... looks more promising , so it is pursued , generating nodes G and H. But again when these new nodes are evaluated they look less promising than another path , so attention is returned to the path through D to E. E is then expanded ...
... looks more promising , so it is pursued , generating nodes G and H. But again when these new nodes are evaluated they look less promising than another path , so attention is returned to the path through D to E. E is then expanded ...
Página 548
... look like this : If : the most current active context is distributing massbus devices , and there is a single - port disk drive that has not been assigned to a massbus , and there are no unassigned dual - port disk drives , and the ...
... look like this : If : the most current active context is distributing massbus devices , and there is a single - port disk drive that has not been assigned to a massbus , and there are no unassigned dual - port disk drives , and the ...
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