Investigating Explanation-Based Learning
By: edited by Gerald DeJong
Series: The Springer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems -- 120; Springer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems -- 120.
Publisher: Springer US
Published: 1993
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] /
Number of pages: 438
ISBN-13: 9781461366003; 9781461536024
Subjects: Computer science; Artificial intelligence
Description: 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.
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