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Modeling category learning using a dual-system approach: A simulation ofShepard, Hovland and Jenkins (1961) by COVIS

Abstract

This paper examines the ability of a dual-system, formal modelof categorization COVIS (Ashby, Paul & Maddox, 2011) topredict the learning performance of participants on the six cat-egory structures described in Shepard, Hovland and Jenkin’s(1961) seminal study. COVIS assumes that category learningis mediated by two dissociable neural systems that compete tocontrol responding. The verbal system explicitly tests verbal-izable rules, whereas the implicit system gradually associateseach stimulus with the appropriate response. Although COVISis highly influential, there are no published evaluations of theformal model against classic category learning data (COVIS ismost typically applied heuristically to the design of new exper-iments). In the current paper, we begin to address this gap inthe literature. Specifically, we demonstrate that COVIS is ableto accommodate the ordinal pattern found by Shepard et al.,provided that adjustments consistent with the model’s theoret-ical framework are made.

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