How the bayesians got their beliefs (and what those beliefs actually are): Comment on bowers and davis (2012)

Thomas L. Griffiths; Nick Chater; Dennis Norris; Alexandre Pouget

doi:10.1037/a0026884

How the bayesians got their beliefs (and what those beliefs actually are): Comment on bowers and davis (2012)

Thomas L. Griffiths, Nick Chater, Dennis Norris, Alexandre Pouget

Research output: Contribution to journal › Comment/debate › peer-review

102 Scopus citations

Abstract

Bowers and Davis (2012) criticize Bayesian modelers for telling "just so" stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific alternatives. We address these points by clarifying our beliefs about the goals and status of Bayesian models and by identifying what we view as the unique merits of the Bayesian approach.

Original language	English (US)
Pages (from-to)	415-422
Number of pages	8
Journal	Psychological Bulletin
Volume	138
Issue number	3
DOIs	https://doi.org/10.1037/a0026884
State	Published - May 2012
Externally published	Yes

All Science Journal Classification (ASJC) codes

General Psychology

Keywords

Bayesian inference
Computational neuroscience
Probabilistic models
Theoretical frameworks

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10.1037/a0026884

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abstract = "Bowers and Davis (2012) criticize Bayesian modelers for telling {"}just so{"} stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific alternatives. We address these points by clarifying our beliefs about the goals and status of Bayesian models and by identifying what we view as the unique merits of the Bayesian approach.",

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AU - Norris, Dennis

AU - Pouget, Alexandre

PY - 2012/5

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AB - Bowers and Davis (2012) criticize Bayesian modelers for telling "just so" stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific alternatives. We address these points by clarifying our beliefs about the goals and status of Bayesian models and by identifying what we view as the unique merits of the Bayesian approach.

KW - Bayesian inference

KW - Computational neuroscience

KW - Probabilistic models

KW - Theoretical frameworks

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JO - Psychological Bulletin

JF - Psychological Bulletin

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ER -

How the bayesians got their beliefs (and what those beliefs actually are): Comment on bowers and davis (2012)

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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