A tutorial introduction to Bayesian models of cognitive development
Name
Tenenbaum_a tutorial introduction to bayesian.pdf
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672.24 KB
Format
Adobe PDF
Checksum (MD5)
e83f89820146d52876211c099bf484c4
Author(s)
Perfors, Amy
Tenenbaum, Joshua B.
Griffiths, Thomas L.
Xu, Fei
Date Issued
January 2011
Journal
Cognition
Publisher
Elsevier
Citation
Perfors, Amy, Joshua B. Tenenbaum, Thomas L. Griffiths, and Fei Xu. “A Tutorial Introduction to Bayesian Models of Cognitive Development.” Cognition 120, no. 3 (September 2011): 302–321.
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-Noncommercial-NoDerivatives
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.cognition.2010.11.015
