Evaluating Explanations

A Content Theory

David B. Leake

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English

Psychology Press Ltd
02 September 2016

Cognition & cognitive psychology; Artificial intelligence

Series: Artificial Intelligence Series

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 are appropriate. This important view is demonstrated with examples of the performance of ACCEPTER, a computer system for story understanding, anomaly detection, and explanation evaluation.

By: David B. Leake
Imprint: Psychology Press Ltd
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 152mm,
Weight: 453g
ISBN: 9781138969162
ISBN 10: 1138969168
Series: Artificial Intelligence Series
Pages: 274
Publication Date: 02 September 2016
Audience: Professional and scholarly , Professional and scholarly , Undergraduate , Undergraduate
Format: Paperback
Publisher's Status: Active

Authored by Leake, David B.