Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Bayesian brains without probabilities

Tools
- Tools
+ Tools

Sanborn, Adam N. and Chater, Nick (2016) Bayesian brains without probabilities. Trends in Cognitive Sciences, 20 (12). pp. 883-893. doi:10.1016/j.tics.2016.10.003 ISSN 1364-6613.

[img] PDF
WRAP_PIIS1364661316301565.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons Attribution 4.0.

Download (2121Kb)
Official URL: http://dx.doi.org/10.1016/j.tics.2016.10.003

Request Changes to record.

Abstract

Bayesian explanations have swept through cognitive science over the past two decades, from intuitive physics and causal learning, to perception, motor control and language. Yet people flounder with even the simplest probability questions. What explains this apparent paradox? How can a supposedly Bayesian brain reason so poorly with probabilities? In this paper, we propose a direct and perhaps unexpected answer: that Bayesian brains need not represent or calculate probabilities at all and are, indeed, poorly adapted to do so. Instead, the brain is a Bayesian sampler. Only with infinite samples does a Bayesian sampler conform to the laws of probability; with finite samples it systematically generates classic probabilistic reasoning errors, including the unpacking effect, base-rate neglect, and the conjunction fallacy.

Item Type: Journal Article
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: Faculty of Social Sciences > Warwick Business School > Behavioural Science
Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH): Bayesian statistical decision theory, Cognitive science
Journal or Publication Title: Trends in Cognitive Sciences
Publisher: Elsevier Science
ISSN: 1364-6613
Official Date: December 2016
Dates:
DateEvent
December 2016Published
26 October 2016Available
5 October 2016Accepted
Volume: 20
Number: 12
Page Range: pp. 883-893
DOI: 10.1016/j.tics.2016.10.003
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 27 October 2016
Date of first compliant Open Access: 28 October 2016
Funder: Economic and Social Research Council (Great Britain) (ESRC), European Research Council (ERC), Leverhulme Trust (LT), Research Councils UK (RCUK)
Grant number: ES/K004948/1, ES/K002201/1 (ESRC), 295917-RATIONALITY (ERC), RP2012-V-022 (Leverhulme Trust), EP/K039830/1 (RCUK)

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us