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Investigating Explanation-Based Learning : The Springer International Series in Engineering and Computer Science - Gerald DeJong

Investigating Explanation-Based Learning

The Springer International Series in Engineering and Computer Science

By: Gerald DeJong (Editor)

Hardcover

Published: 31st October 1992
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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.

Preface
Foreword
A Perspective on Explanation-Based Learningp. 1
Explanation Generalization in EGGSp. 20
Generalizing Explanation Structuresp. 60
Recoverable Simplifications and the Intractable Domain Theory Problemp. 128
Designing Experiments to Extend the Domain Theoryp. 166
Some Aspects of Operationalityp. 190
Empirically Evaluating EBLp. 222
Psychological Studies of Explanation-Based Learningp. 295
Case Study 1 - ARMS: Acquiring Robotic Assembly Plansp. 317
Case Study 2 - GENESIS: Learning Schemata for Narrative Text Understandingp. 343
Case Study 3 - PHYSICS 101: Learning in Mathematically Based Domainsp. 372
Case Study 4 - ADEPT: Extending the Domain Theoryp. 395
Case Study 5 - NONMON: Learning with Recoverable Simplificationsp. 410
Case Study 6 - GRASPER: Learning to Manipulate an Uncertain Worldp. 424
Indexp. 435
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9780792391258
ISBN-10: 079239125X
Series: The Springer International Series in Engineering and Computer Science
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 438
Published: 31st October 1992
Publisher: Springer
Country of Publication: NL
Dimensions (cm): 23.5 x 15.5  x 2.5
Weight (kg): 1.78