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Testing the efficiency of Markov Chain Monte Carlo with people using facial affect categories
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Martin, J. B., Griffiths, Thomas L. and Sanborn, Adam N. (2012) Testing the efficiency of Markov Chain Monte Carlo with people using facial affect categories. Cognitive Science, 36 (11). pp. 150-162. doi:10.1111/j.1551-6709.2011.01204.x ISSN 0364-0213.
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Official URL: http://dx.doi.org/10.1111/j.1551-6709.2011.01204.x
Abstract
Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as images is methodologically challenging. Recent work has produced methods for identifying these representations from observed behavior, such as reverse correlation (RC). We compare RC against an alternative method for inferring the structure of natural categories called Markov chain Monte Carlo with People (MCMCP). Based on an algorithm used in computer science and statistics, MCMCP provides a way to sample from the set of stimuli associated with a natural category. We apply MCMCP and RC to the problem of recovering natural categories that correspond to two kinds of facial affect (happy and sad) from realistic images of faces. Our results show that MCMCP requires fewer trials to obtain a higher quality estimate of people’s mental representations of these two categories.
Item Type: | Journal Article | ||||
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Subjects: | B Philosophy. Psychology. Religion > BF Psychology R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Psychology | ||||
Library of Congress Subject Headings (LCSH): | Markov processes -- Testing, Monte Carlo method, Categorization (Psychology) -- Testing, Cognition -- Testing | ||||
Journal or Publication Title: | Cognitive Science | ||||
Publisher: | Wiley-Blackwell Publishing, Inc. | ||||
ISSN: | 0364-0213 | ||||
Official Date: | January 2012 | ||||
Dates: |
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Volume: | 36 | ||||
Number: | 11 | ||||
Page Range: | pp. 150-162 | ||||
DOI: | 10.1111/j.1551-6709.2011.01204.x | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 6 April 2017 | ||||
Date of first compliant Open Access: | 6 April 2017 | ||||
Funder: | National Science Foundation (U.S.), Robert & Colleen Haas | ||||
Grant number: | IIS-0845410 (NSF) |
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