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Bayesian models of cognition

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Chater, Nick, Oaksford, M. (Mike), Hahn, Ulrike and Heit, Evan (2010) Bayesian models of cognition. Wiley Interdisciplinary Reviews: Cognitive Science, Vol.1 (No.6). pp. 811-823. doi:10.1002/wcs.79 ISSN 1939-5078.

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Official URL: http://dx.doi.org/10.1002/wcs.79

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Abstract

There has been a recent explosion in research applying Bayesian models to cognitive phenomena. This development has resulted from the realization that across a wide variety of tasks the fundamental problem the cognitive system confronts is coping with uncertainty. From visual scene recognition to on-line language comprehension, from categorizing stimuli to determining to what degree an argument is convincing, people must deal with the incompleteness of the information they possess to perform these tasks, many of which have important survival-related consequences. This paper provides a review of Bayesian models of cognition, dividing them up by the different aspects of cognition to which they have been applied. The paper begins with a brief review of Bayesian inference. This falls short of a full technical introduction but the reader is referred to the relevant literature for further details. There follows reviews of Bayesian models in Perception, Categorization, Learning and Causality, Language Processing, Inductive Reasoning, Deductive Reasoning, and Argumentation. In all these areas, it is argued that sophisticated Bayesian models are enhancing our understanding of the underlying cognitive computations involved. It is concluded that a major challenge is to extend the evidential basis for these models, especially to accounts of higher level cognition.

Item Type: Journal Article
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Social Sciences > Warwick Business School > Behavioural Science
Faculty of Social Sciences > Warwick Business School
Journal or Publication Title: Wiley Interdisciplinary Reviews: Cognitive Science
Publisher: John Wiley & Sons Ltd.
ISSN: 1939-5078
Official Date: 2010
Dates:
DateEvent
2010Published
Volume: Vol.1
Number: No.6
Number of Pages: 13
Page Range: pp. 811-823
DOI: 10.1002/wcs.79
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

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