✦ LIBER ✦
An extension of the exemplar-based random-walk model to separable-dimension stimuli
✍ Scribed by Andrew L. Cohen; Robert M. Nosofsky
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 307 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0022-2496
No coin nor oath required. For personal study only.
✦ Synopsis
An extension of Nosofsky and Palmeri's (Psychol. Rev. 104 (1997a)
- exemplar-based random-walk (EBRW) model of categorization is presented as a model of the time course of categorization of separable-dimension stimuli. Nosofsky and Palmeri (1997a) assumed that the perceptual encoding of all stimuli was identical. However, in the current model, we assume as in Lamberts (J. Exp. Psychol.: General 124 (1995) 161) that the inclusion of individual stimulus dimensions into the similarity calculations is a stochastic process with the probability of inclusion based on the perceptual salience of the dimensions. Thus, the exemplars that enter into the random-walk change dynamically during the time course of processing. This model is implemented as a Markov chain. Its predictions are compared with alternative models in a speeded categorization experiment with separable-dimension stimuli.