Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
926950 | Cognition | 2011 | 20 Pages |
Abstract
We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive development. Our goal is to provide an intuitive and accessible guide to the what, the how, and the why of the Bayesian approach: what sorts of problems and data the framework is most relevant for, and how and why it may be useful for developmentalists. We emphasize a qualitative understanding of Bayesian inference, but also include information about additional resources for those interested in the cognitive science applications, mathematical foundations, or machine learning details in more depth. In addition, we discuss some important interpretation issues that often arise when evaluating Bayesian models in cognitive science.
Keywords
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Cognitive Neuroscience
Authors
Amy Perfors, Joshua B. Tenenbaum, Thomas L. Griffiths, Fei Xu,