On the nature of implicit categorization.
Current categorization models disagree about whether people make a priori assumptions about the structure of unfamiliar categories. Data from two experiments provided strong evidence that people do not make such assumptions. These results rule out prototype models and many decision bound models of categorization. We review previously published neuropsychological results that favor the assumption that category learning relies on a procedural-memory-based system, rather than on an instance-based system (as is assumed by exemplar models). On the basis of these results, a new category-learning model is proposed that makes no a priori assumptions about category structure and that relies on procedural learning and memory.
Department of Psychology, University of California, Santa Barbara, CA 93106, USA. ashby@psych.ucsb.edu
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Ashby
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Waldron
D002965:Classification; D006801:Humans; D007858:Learning / Q000502:physiology; D016013:Likelihood Functions; D008568:Memory / Q000502:physiology; D008960:Models, Psychological; D015233:Models, Statistical; D009482:Neurophysiology