… , many of which have important survival-related consequences. This paper provides a
review of Bayesian models of cognition, dividing them up by the different aspects of cognition to …

… account of how rational agents should reason in situations of … the kinds of computational
models of cognition that we can … of Bayesian probabilistic inference, and to explain some of the …

… of Bayesian inference. This paper presents a tutorial overview of the Bayesian framework for
studying cognitive … , and the why of the Bayesian approach: what sorts of problems and data …

… Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive
power of current Bayesian models, … to offer substantive explanations of cognition. We lay out …

… Bayesian modeling provides a flexible and interpretable way of extending simple models of
cognitive … we discuss four of the most important potential hierarchical Bayesian contributions. …

… We conclude by outlining some challenges for Bayesian models of human cognition that
will need to be addressed by future research. WIREs Cogn Sci 2011 2 8–21 DOI: 10.1002/wcs.…

… The goal of this book is to facilitate and promote the use of Bayesian modeling in cognitive
… As shown by means of examples throughout this book, Bayesian modeling is ideally suited …

… of either kind of Bayesian model—normative standards and descriptive models are both
useful tools for cognitive scientists—but to try to highlight the importance of maintaining a clear …

… The use of Bayesian methods to implement, apply, and evaluate cognitive models is the
focus of this chapter. Advantages of Bayesian Methods …

… All of the Bayesian models in this article rely on posterior sampling from graphical models
(see Griffiths, Kemp, & Tenenbaum, in press, and Jordan, 2004, for psychological and …