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Journal Article

Representation, abstraction, and simple-minded sophisticates

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Dayan,  P
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/representation-abstraction-and-simpleminded-sophisticates/613BB16F12E2ACC854DBC162E389863C
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Citation

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


Cite as: https://hdl.handle.net/21.11116/0000-0006-C0FA-7
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.