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  Representation, abstraction, and simple-minded sophisticates

Dayan, P. (2020). Representation, abstraction, and simple-minded sophisticates. Behavioral and Brain Sciences, 43: e126. doi:10.1017/S0140525X19002942.

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 Creators:
Dayan, P1, 2, Author           
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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 Dates: 2020-06
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1017/S0140525X19002942
eDoc: e126
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Title: Behavioral and Brain Sciences
Source Genre: Journal
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Publ. Info: New York : Cambridge University Press.
Pages: - Volume / Issue: 43 Sequence Number: e126 Start / End Page: - Identifier: ISSN: 0140-525X
CoNE: https://pure.mpg.de/cone/journals/resource/954925341730