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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
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: |
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| 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| Status: | Not Peer Reviewed | ||||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 | ||||
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