ERIC Number: EJ849131
Record Type: Journal
Publication Date: 2007-May
Abstractor: As Provided
Reference Count: 49
The Bayesian Revolution Approaches Psychological Development
Shultz, Thomas R.
Developmental Science, v10 n3 p357-364 May 2007
This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and provides evidence that children's performance can be optimal in a Bayesian sense. There remains much to be done in terms of understanding how representations are created, how development occurs, how Bayesian computation might be neurally implemented, and in reconciling the new work with older evidence that even skilled adults are incompetent Bayesians.
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Publication Type: Journal Articles; Opinion Papers
Education Level: N/A
Authoring Institution: N/A