Artificial Intelligence |
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An EBL system attempts to learn from a single example x by explaining why x is
an example of the target concept . The explanation is then generalized , and the
system ' s performance is improved through the availability of this knowledge .
An EBL system attempts to learn from a single example x by explaining why x is
an example of the target concept . The explanation is then generalized , and the
system ' s performance is improved through the availability of this knowledge .
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 477
If there is a set whose complement is much rarer than itself , then create a new
concept representing the complement . There is a strong analogy between
addition and multiplication of natural numbers . But that analogy breaks down
when we ...
If there is a set whose complement is much rarer than itself , then create a new
concept representing the complement . There is a strong analogy between
addition and multiplication of natural numbers . But that analogy breaks down
when we ...
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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