Investigating Explanation-Based Learning:

Explanation-Based Learning (EBL) can generally be viewed as substituting background knowledge for the large training set of exemplars needed by conventional or empirical machine learning systems. The background knowledge is used automatically to construct an explanation of a few training exemplars....

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Bibliographic Details
Other Authors: DeJong, Gerald (Editor)
Format: Electronic eBook
Language:English
Published: Boston, MA Springer US 1993
Series:The Springer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems 120
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Online Access:BTU01
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Summary:Explanation-Based Learning (EBL) can generally be viewed as substituting background knowledge for the large training set of exemplars needed by conventional or empirical machine learning systems. The background knowledge is used automatically to construct an explanation of a few training exemplars. The learned concept is generalized directly from this explanation. The first EBL systems of the modern era were Mitchell's LEX2, Silver's LP, and De Jong's KIDNAP natural language system. Two of these systems, Mitchell's and De Jong's, have led to extensive follow-up research in EBL. This book outlines the significant steps in EBL research of the Illinois group under De Jong. This volume describes theoretical research and computer systems that use a broad range of formalisms: schemas, production systems, qualitative reasoning models, non-monotonic logic, situation calculus, and some home-grown ad hoc representations. This has been done consciously to avoid sacrificing the ultimate research significance in favor of the expediency of any particular formalism. The ultimate goal, of course, is to adopt (or devise) the right formalism
Physical Description:1 Online-Ressource (IX, 438 p)
ISBN:9781461536024
DOI:10.1007/978-1-4615-3602-4

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