The Library
Types of approximation for probabilistic cognition : sampling and variational
Tools
Sanborn, Adam N. (2017) Types of approximation for probabilistic cognition : sampling and variational. Brain and cognition, 112 . pp. 98-101. doi:10.1016/j.bandc.2015.06.008 ISSN 0278-2626.
|
PDF
WRAP_1-s2.0-S0278262615300038-main.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (402Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.bandc.2015.06.008
Abstract
A basic challenge for probabilistic models of cognition is explaining how probabilistically correct solutions are approximated by the limited brain, and how to explain mismatches with human behavior. An emerging approach to solving this problem is to use the same approximation algorithms that were been developed in computer science and statistics for working with complex probabilistic models. Two types of approximation algorithms have been used for this purpose: sampling algorithms, such as importance sampling and Markov chain Monte Carlo, and variational algorithms, such as mean-field approximations and assumed density filtering. Here I briefly review this work, outlining how the algorithms work, how they can explain behavioral biases, and how they might be implemented in the brain. There are characteristic differences between how these two types of approximation are applied in brain and behavior, which points to how they could be combined in future research.
Item Type: | Journal Article | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Subjects: | B Philosophy. Psychology. Religion > BF Psychology | ||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Psychology | ||||||||||
Library of Congress Subject Headings (LCSH): | Cognition -- Mathematical models | ||||||||||
Journal or Publication Title: | Brain and cognition | ||||||||||
Publisher: | Academic Press Inc. ; Elsevier Science | ||||||||||
ISSN: | 0278-2626 | ||||||||||
Official Date: | March 2017 | ||||||||||
Dates: |
|
||||||||||
Volume: | 112 | ||||||||||
Page Range: | pp. 98-101 | ||||||||||
DOI: | 10.1016/j.bandc.2015.06.008 | ||||||||||
Status: | Peer Reviewed | ||||||||||
Publication Status: | Published | ||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||
Date of first compliant deposit: | 30 December 2015 | ||||||||||
Date of first compliant Open Access: | 30 December 2015 | ||||||||||
Funder: | Economic and Social Research Council (Great Britain) (ESRC) | ||||||||||
Grant number: | ES/K004948/1 (EPSRC) | ||||||||||
Adapted As: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year