Evaluating Explanations - A Content Theory (Hardcover)

David B. Leake

Series: Artificial Intelligence Series

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Psychology and philosophy have long studied the nature and role of explanation. More recently, artificial intelligence research has developed promising theories of how explanation facilitates learning and generalization. By using explanations to guide learning, explanation-based methods allow reliable learning of new concepts in complex situations, often from observing a single example.
The author of this volume, however, argues that explanation-based learning research has neglected key issues in explanation construction and evaluation. By examining the issues in the context of a story understanding system that explains novel events in news stories, the author shows that the standard assumptions do not apply to complex real-world domains. An alternative theory is presented, one that demonstrates that context -- involving both explainer beliefs and goals -- is crucial in deciding an explanation's goodness and that a theory of the possible contexts can be used to determine which explanations areappropriate. This important view is demonstrated with examples of the performance of ACCEPTER, a computer system for story understanding, anomaly detection, and explanation evaluation.

General

Imprint:	Psychology Press
Country of origin:	United States
Series:	Artificial Intelligence Series
Release date:	April 1992
First published:	1992
Authors:	David B. Leake
Dimensions:	229 x 152 x 20mm (L x W x T)
Format:	Hardcover
Pages:	274
ISBN-13:	978-0-8058-1064-6
Categories:	Books > Social sciences > Psychology > Cognition & cognitive psychology > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	0-8058-1064-1
Barcode:	9780805810646