An exemplar-based random walk model of speeded classification.

Nosofsky RM, Palmeri TJ
Psychol Rev. 1997 104 (2): 266-300

PMID: 9127583 · DOI:10.1037/0033-295x.104.2.266

The authors propose and test an exemplar-based random walk model for predicting response times in tasks of speeded, multidimensional perceptual classification. The model combines elements of R. M. Nosofsky's (1986) generalized context model of categorization and G. D. Logan's (1988) instance-based model of automaticity. In the model, exemplars race among one another to be retrieved from memory, with rates determined by their similarity to test items. The retrieved exemplars provide incremental information that enters into a random walk process for making classification decisions. The model predicts correctly effects of within- and between-categories similarity, individual-object familiarity, and extended practice on classification response times. It also builds bridges between the domains of categorization and automaticity.

MeSH Terms (8)

Concept Formation Cues Decision Making Humans Memory Models, Psychological Perception Stochastic Processes

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