Why and How to Learn Why: Analysis-Based Generalization of Procedures.

Abstract

Computer learners often develop explanations of events they observe during training. Recent work on generalization suggests that explanations may be valuable in permitting learners to develop generalizations from one or a few examples. We explore this idea by describing four generalization paradigms in which explanations play a part: explanation-based generalization (EBG), structure mapping analogical generalization (SMAG), modificational analogical generalization (MAG) and synthetic generalization (SG). We describe a model, the EXPL system, capable of applying MAG or SG to the generalization of simple procedures in human-computer interaction. We present evidence that EXPL's analysis procedure, which constructs explanations as needed by MAG or SG, embodies heuristic principles used by human learners, and that MAG provides a good account of some human generalization, when retention of examples is not a problem.

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Document Details

Document Type
Technical Report
Publication Date
Aug 26, 1986
Accession Number
ADA178200

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  • Clayton Lewis

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  • University of Colorado Boulder

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