Knowledge partitioning in categorization: Constraints on exemplar models

Lee Xieng Yang, Stephan Lewandowsky*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

41 Citations (Scopus)

Abstract

The authors present 2 experiments that establish the presence of knowledge partitioning in perceptual categorization. Many participants learned to rely on a cue, context which did not predict category membership but identified partial boundaries, to gate independent partial categorization strategies. When participants partitioned their knowledge, a strategy used in 1 context was unaffected by knowledge demonstrably present in other contexts. An exemplar model, attentional learning covering map, was shown to be unable to accommodate knowledge partitioning. Instead, a mixture-of-experts model, attention to rules and instances in a unified model (ATRIUM), could handle the results. The success of ATRIUM resulted from its assumption that people memorize not only exemplars but also the way in which they are to be classified.

Original languageEnglish
Pages (from-to)1045-1064
Number of pages20
JournalJournal of Experimental Psychology: Learning, Memory, and Cognition
Volume30
Issue number5
DOIs
Publication statusPublished - Sep 2004

Structured keywords

  • Memory

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