A tutorial introduction to Bayesian models of cognitive development

Amy Perfors, Joshua B. Tenenbaum, Thomas L. Griffiths, Fei Xu

Research output: Contribution to journalArticle

105 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)302-321
Number of pages20
JournalCognition
Volume120
Issue number3
DOIs
StatePublished - Sep 2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Language and Linguistics
  • Developmental and Educational Psychology
  • Linguistics and Language
  • Cognitive Neuroscience

Keywords

  • Bayesian models
  • Cognitive development

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