The strengths of - And some of the challenges for - Bayesian models of cognition

Thomas L. Griffiths

doi:10.1017/S0140525X0900034X

The strengths of - And some of the challenges for - Bayesian models of cognition

Thomas L. Griffiths

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

2 Scopus citations

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.

Original language	English (US)
Pages (from-to)	89-90
Number of pages	2
Journal	Behavioral and Brain Sciences
Volume	32
Issue number	1
DOIs	https://doi.org/10.1017/S0140525X0900034X
State	Published - 2009
Externally published	Yes

All Science Journal Classification (ASJC) codes

Neuropsychology and Physiological Psychology
Physiology
Behavioral Neuroscience

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10.1017/S0140525X0900034X

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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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The strengths of - And some of the challenges for - Bayesian models of cognition

Abstract

All Science Journal Classification (ASJC) codes

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