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Bayesian models of cognition

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Sanborn, Adam N. (2015) Bayesian models of cognition. In: Jaeger, Dieter and Jung, Ranu, (eds.) Encyclopedia of Computational Neuroscience. Springer, pp. 624-625. ISBN 9781461466758

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Official URL: http://doi.org/10.1007/978-1-4614-6675-8_447

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Abstract

Bayesian models provide a principled way to deal with uncertainty. In cognitive tasks the uncertainty is mainly in how to represent the observed data, as there is usually not enough data to uniquely determine the representation. Bayesian models of cognition implement a general method for dealing with representational uncertainty which can be applied to explain human performance in various cognitive tasks.

Item Type: Book Item
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: Faculty of Science, Engineering and Medicine > Science > Psychology
Publisher: Springer
ISBN: 9781461466758
Book Title: Encyclopedia of Computational Neuroscience
Editor: Jaeger, Dieter and Jung, Ranu
Official Date: 24 March 2015
Dates:
DateEvent
24 March 2015Published
Page Range: pp. 624-625
DOI: 10.1007/978-1-4614-6675-8_447
Status: Not Peer Reviewed
Publication Status: Published
Date of first compliant deposit: 16 March 2017
Related URLs:
  • http://www.worldcat.org/oclc/908611469

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