Behavioral and Brain Sciences
- Behavioral and Brain Sciences / Volume 32 / Issue 01 / February 2009, pp 89-90
- Copyright © Cambridge University Press 2009
- DOI: http://dx.doi.org/10.1017/S0140525X0900034X (About DOI), Published online: 12 February 2009
Open Peer Commentary
The strengths of – and some of the challenges for – Bayesian models of cognition
Thomas L. Griffithsa1
a1 Department of Psychology, University of California, Berkeley, Berkeley, CA 94720-1650. tom_griffiths@berkeley.edu http://cocosci.berkeley.edu
Abstract
Bayesian Rationality (Oaksford & Chater 2007) illustrates the strengths of Bayesian models of cognition: the systematicity of rational explanations, transparent assumptions about human learners, and combining structured symbolic representation with statistics. However, the book also highlights some of the challenges this approach faces: of providing psychological mechanisms, explaining the origins of the knowledge that guides human learning, and accounting for how people make genuinely new discoveries.
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- Précis of Bayesian Rationality: The Probabilistic Approach to Human Reasoning
