Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 260
... properties that its elements possess . We want to use inheritance to infer those properties from general knowledge about the set . But a class is also an entity in itself . It may possess properties that belong not to the individual ...
... properties that its elements possess . We want to use inheritance to infer those properties from general knowledge about the set . But a class is also an entity in itself . It may possess properties that belong not to the individual ...
Página 263
... properties . Some of the properties we would like to be able to represent and use in reasoning include : • The classes to which the attribute can be attached , i.e. , for what classes does it make sense ? For example , weight makes ...
... properties . Some of the properties we would like to be able to represent and use in reasoning include : • The classes to which the attribute can be attached , i.e. , for what classes does it make sense ? For example , weight makes ...
Página 293
... properties include things like number - of - legs . Objects tend to inherit their extrinsic properties from IndividualObjects . Event and Process - An Event is anything with temporal extent , e.g. , Walking . Process is a subclass of ...
... properties include things like number - of - legs . Objects tend to inherit their extrinsic properties from IndividualObjects . Event and Process - An Event is anything with temporal extent , e.g. , Walking . Process is a subclass of ...
Contenido
Weak SlotandFiller Structures | 9 |
6 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
Abbott algorithm answer apply approach Artificial Intelligence assertions attributes axioms backpropagation backtracking backward backward reasoning belief best-first search breadth-first search Cabot Caesar Chapter clauses concept consider constraints contains contexts contradiction corresponding define depth-first depth-first search described discussed domain example explicitly fact given goal graph heuristic heuristic function Horn clauses important inference inheritance input instance interpretation justification knowledge base knowledge representation labeled learning logical assertions Marcus match move MYCIN node nonmonotonic reasoning object operators particular path perceptron possible preconditions predicate logic problem problem-solving procedure produce production system PROLOG propagation propositional logic question represent resolution result robot rules Section semantic semantic net sentence shown in Figure simple slot solution solve space specific statements step strategy structure Suppose suspect syntactic task techniques theorem things tree true truth maintenance system variables wff's