Unsupervised concept learning and value systematicity: a complex whole aids learning the parts.

Abstract

Ease of learning new concepts may best be understood by simultaneously considering models of learning and theories of how "good" systems of categories are organized. The authors tested the effects on learning of value systematicity, a proposed organizing principle: If 1 attribute is predictive of another, it should predict still more. This principle derives from focused sampling in the internal feedback model (D. Billman & E. Heit, 1988) of unsupervised, or observational, learning. In 3 experiments, the authors tested how the organization of structure in input (value systematicity) affected unsupervised learning of categories about alien animals. Across all experiments, learning a target rule was easier in conditions with high value systematicity, relative to several low systematicity controls. The authors compare results to predictions of several learning models and consider the links between learning and the resulting category structure.