Pinning down the theoretical commitments of Bayesian cognitive models

Mathematical developments in probabilistic inference have led to optimism over the prospects for Bayesian models of cognition. Our target article calls for better differentiation of these technical developments from theoretical contributions. It distinguishes between Bayesian Fundamentalism, which i...

Full description

Saved in:
Bibliographic Details
Published in:The Behavioral and brain sciences 2011-08, Vol.34 (4), p.215-231
Main Authors: Jones, Matt, Love, Bradley C.
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Cognitive ability
Cognitive models
Computer applications
Hypotheses
Mathematical models
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Mathematical developments in probabilistic inference have led to optimism over the prospects for Bayesian models of cognition. Our target article calls for better differentiation of these technical developments from theoretical contributions. It distinguishes between Bayesian Fundamentalism, which is theoretically limited because of its neglect of psychological mechanism, and Bayesian Enlightenment, which integrates rational and mechanistic considerations and is thus better positioned to advance psychological theory. The commentaries almost uniformly agree that mechanistic grounding is critical to the success of the Bayesian program. Some commentaries raise additional challenges, which we address here. Other commentaries claim that all Bayesian models are mechanistically grounded, while at the same time holding that they should be evaluated only on a computational level. We argue this contradictory stance makes it difficult to evaluate a model's scientific contribution, and that the psychological commitments of Bayesian models need to be made more explicit.
ISSN:0140-525X
1469-1825
DOI:10.1017/S0140525X11001439