Artificial Intelligence |
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Página 265
It maps from elements of its domain ( the classes for which it makes sense ) to
elements of its range ( its possible values ) . A relation is a set of ordered pairs .
Thus it makes sense to say that one relation ( R1 ) is a subset of another ( R2 ) .
It maps from elements of its domain ( the classes for which it makes sense ) to
elements of its range ( its possible values ) . A relation is a set of ordered pairs .
Thus it makes sense to say that one relation ( R1 ) is a subset of another ( R2 ) .
Página 473
During the first step , the domain theory is used to prune away all the unimportant
aspects of the training example with respect to the goal concept . What is left is an
explanation of why the training example is an instance of the goal concept .
During the first step , the domain theory is used to prune away all the unimportant
aspects of the training example with respect to the goal concept . What is left is an
explanation of why the training example is an instance of the goal concept .
Página 547
To solve expert - level problems , expert systems need access to a substantial
domain knowledge base , which must be built as efficiently as possible . They
also need to exploit one or more reasoning mechanisms to apply their
knowledge to ...
To solve expert - level problems , expert systems need access to a substantial
domain knowledge base , which must be built as efficiently as possible . They
also need to exploit one or more reasoning mechanisms to apply their
knowledge to ...
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Contenido
What Is Artificial Intelligence? | 3 |
Problems Problem Spaces and Search | 29 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
active addition agents algorithm allow answer apply approach assertions becomes belief build called Chapter clauses combined complete concept consider consistent constraints contains corresponding define dependency described discussed domain elements example fact Figure function given goal heuristic important initial input instance interpretation John kinds knowledge knowledge base labeled language learning logic look match meaning methods move natural necessary node object occur operators output particular path perform position possible predicate present problem procedure produce properties question reasoning relation represent representation result robot rules semantic sentence shown in Figure shows simple single situation slot solution solve space specific statements step stored structure Suppose task techniques things tree true understanding units usually variables weights