For questions about the Bayesian framework for cognitive modeling. The field is concerned with studying the effectiveness of modeling humans as Bayesian agents, and inferring their mental states based on these models. For general Bayesian inference as used in statistics, use the statistics tag.

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22
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What are some of the drawbacks to probabilistic models of cognition?

Probabilistic approaches to modelling cognition are increasing in popularity and being encouraged within the field (Chater, Tanenbaum, & Yuille, 2006). What are some of the arguments against or ...
14
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2answers
1k views

What tasks does Bayesian decision-making model poorly?

Bayesianism has been a relatively successful paradigm for modeling decision-making. However, not every psychologist is a bayesian, and there are tasks such as the Tversky & Shafir (1992) ...
11
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2answers
473 views

Biological plausibility of bayesian models of cognition

Inspired by this question: What are drawbacks to probabilistic models of cognition? I would like to know more about the biological plausibility of Bayesian models of cognition. Is there any neural ...
7
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3answers
402 views

Introductory resources on bayesian modeling for cognitive sciences

On Cross Validated there is a great question about best introductory books for bayesian statistics. Also, Jeromy Anglim blogged recently about use of JAGS, rjags, and Bayesian Modelling, with some ...
10
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2answers
230 views

How can the success of Bayesian models be reconciled with demonstrations of heuristic and biased reasoning?

In recent years, Bayesian models of cognition have been used - with considerable success - to explain human reasoning in a variety of inferential tasks (Chater, Tenenbaum, & Yuille, 2006). These ...