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A model of probabilistic category learning

Kruschke, John K. and Johansen, Mark K. 1999. A model of probabilistic category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition 25 (5) , pp. 1083-1119. 10.1037/0278-7393.25.5.1083

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Abstract

A new connectionist model (named RASHNL) accounts for many "irrational" phenomena found in nonmetric multiple-cue probability learning, wherein people learn to utilize a number of discrete-valued cues that are partially valid indicators of categorical outcomes. Phenomena accounted for include cue competition, effects of cue salience, utilization of configural information, decreased learning when information is introduced after a delay, and effects of base rates. Experiments 1 and 2 replicate previous experiments on cue competition and cue salience, and fits of the model provide parameter values for making qualitatively correct predictions for many other situations. The model also makes 2 new predictions, confirmed in Experiments 3 and 4. The model formalizes 3 explanatory principles: rapidly shifting attention with learned shifts, decreasing learning rates, and graded similarity in exemplar representation.

Item Type: Article
Status: Published
Schools: Psychology
Publisher: American Psychological Association
ISSN: 0278-7393
Last Modified: 04 Jun 2017 04:15
URI: https://orca.cardiff.ac.uk/id/eprint/35370

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