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In E. M. Pothos & A.J. Wills (Eds.), Formal approaches in categorization. New York: Cambridge University Press. F. Gregory Ashby, Erick J. Paul
 

Summary: In E. M. Pothos & A.J. Wills (Eds.), Formal approaches in categorization. New York: Cambridge University Press.
COVIS
F. Gregory Ashby, Erick J. Paul
Department of Psychology, University of California, Santa Barbara
W. Todd Maddox
Department of Psychology, University of Texas, Austin
The COVIS model of category learning assumes separate rule-based and procedural-learning categorization
systems that compete for access to response production. The rule-based system selects and tests simple
verbalizable hypotheses about category membership. The procedural-learning system gradually associates
categorization responses with regions of perceptual space via reinforcement learning.
Description and Motivation of COVIS.
Despite the obvious importance of categorization to
survival, and the varied nature of category-learning
problems facing every animal, research on category
learning has been narrowly focused (e.g., Markman &
Ross, 2003). For example, the majority of category-
learning studies have focused on situations in which two
categories are relevant, the motor response is fixed, the
nature and timing of feedback is constant (or ignored),
and the only task facing the participant is the relevant

  

Source: Ashby, F. Gregory - Department of Psychology, University of California at Santa Barbara
Maddox, W. Todd - Department of Psychology, University of Texas at Austin

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences