Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 115
... attributes of objects so basic that they occur in almost every problem domain ? If there are , we need to make sure that they are handled appropriately in each of the mechanisms we propose . If such attributes exist , what are they ...
... attributes of objects so basic that they occur in almost every problem domain ? If there are , we need to make sure that they are handled appropriately in each of the mechanisms we propose . If such attributes exist , what are they ...
Página 116
... attributes , we commit to a perspective in which we focus on one object and look for binary relationships between it and others . Attributes are those relationships . So , for example , in Figure 4.5 , we used the attributes instance ...
... attributes , we commit to a perspective in which we focus on one object and look for binary relationships between it and others . Attributes are those relationships . So , for example , in Figure 4.5 , we used the attributes instance ...
Página 117
Elaine Rich. An Isa Hierarchy of Attributes Just as there are classes of objects and specialized subsets of those classes , there are attributes and specializations of attributes . Consider , for example , the attribute height . It is ...
Elaine Rich. An Isa Hierarchy of Attributes Just as there are classes of objects and specialized subsets of those classes , there are attributes and specializations of attributes . Consider , for example , the attribute height . It is ...
Contenido
5 | 24 |
Heuristic Search Techniques | 63 |
Knowledge Representation Issues | 105 |
Derechos de autor | |
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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 fact frame 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 operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG properties 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