Acquiring and Combining Overlapping Concepts

Authors:
Joel D. Martin;Dorrit O. Billman
Affiliations:
Department of Computer Science, University of Pittsburgh, Pittsburgh, PA 15260. martin@cs.pitt.edu;Department of Psychology, Georgia Institute of Technology, Atlanta, GA 30332. billman@pravda.cc.gatech.edu
Venue:
Machine Learning - Special issue on computational models of human learning
Year:
1994

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Abstract

This article presents OLOC, an incremental concept formation system that learns and uses overlapping concepts. OLOC learns probabilistic concepts that have overlapping extensions and does so to maximize expected predictive accuracy. When making predictions, OLOC can combine multiple overlapping concepts.