ABSTRACT: Theorists of human learning, in domains as various as category learning and language acquisition, have grappled with the issue of whether learners induce rules or remember exemplars, or both. In this article we present new data that reflect both rule induction and exemplar encoding, and we present a new connectionist model that specifies one way in which rule-based and exemplar-based mechanisms might interact. Our empirical study was motivated by analogy to past tense acquisition, and specifically by the previous work of Palermo and Howe (1970). Human subjects learned to categorize items, most of which could be classified by a simple rule, except for a few frequently recurring exceptions. The modeling was motivated by the idea of combining an exemplar-based module (ALCOVE, Kruschke 1992) and a rule-based module in a connectionist architecture, and allowing the system to learn which module should be responsible for which instances, using the competitive gating mechanism introduced by Jacobs, Jordan, Nowlan and Hinton (1991). We report quantitative fits of the model to the learning data.