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.
The authors have declared no conflicts of interest for this article.
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 March 2024.
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#6,226,519
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Outputs from Wiley Interdisciplinary Reviews: Cognitive Science
#202
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#71,338
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Outputs of similar age from Wiley Interdisciplinary Reviews: Cognitive Science
#6
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Altmetric has tracked 32,296,133 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 466 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.7. This one has gotten more attention than average, scoring higher than 56% of its peers.
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