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Type: Journal article
Title: Extending the ALCOVE model of category learning to featural stimulus domains
Author: Lee, M.
Navarro, D.
Citation: Psychonomic Bulletin and Review, 2002; 9(1):43-58
Publisher: Psychonomic Soc Inc
Issue Date: 2002
ISSN: 1069-9384
Statement of
Michael D. Lee and Daniel J. Navarro
Abstract: The ALCOVE model of category learning, despite its considerable success in accounting for human performance across a wide range of empirical tasks, is limited by its reliance on spatial stimulus representations. Some stimulus domains are better suited to featural representation, characterizing stimuli in terms of the presence or absence of discrete features, rather than as points in a multidimensional space. We report on empirical data measuring human categorization performance across a featural stimulus domain and show that ALCOVE is unable to capture fundamental qualitative aspects of this performance. In response, a featural version of the ALCOVE model is developed, replacing the spatial stimulus representations that are usually generated by multidimensional scaling with featural representations generated by additive clustering. We demonstrate that this featural version of ALCOVE is able to capture human performance where the spatial model failed, explaining the difference in terms of the contrasting representational assumptions made by the two approaches. Finally, we discuss ways in which the ALCOVE categorization model might be extended further to use "hybrid" representational structures combining spatial and featural components.
Keywords: Humans
Random Allocation
Discrimination Learning
Space Perception
Models, Psychological
Middle Aged
Description: Copyright © 2002 Psychonomic Society, Inc.
DOI: 10.3758/BF03196256
Appears in Collections:Aurora harvest
Environment Institute publications
Psychology publications

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