Citation

Gopnik A, Bonawitz E. Wiley Interdiscip. Rev. Cogn. Sci. 2015; 6(2): 75-86.

Affiliation

Department of Psychology, Rutgers University, Newark, NJ, USA.

Copyright

(Copyright © 2015, John Wiley and Sons)

DOI

10.1002/wcs.1330

PMID

26263064

Abstract

Bayesian models have been applied to many areas of cognitive science including vision, language, and motor learning. We discuss the implications of this framework for cognitive development. We first present a brief introduction to the Bayesian framework. Bayesian models make assumptions about representation explicit, and provide a detailed account of learning. Furthermore, they can provide an account of developmental transitions and other phenomena in development, such as curiosity and exploration. Drawing on recent work bridging empirical developmental data and modeling, we show that these features of the Bayesian approach provide solutions to problems that elude traditional accounts of learning and raise new areas of investigation. WIREs Cogn Sci 2015, 6:75-86. doi: 10.1002/wcs.1330 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article.

Language: en