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  Adaptive Coding of Actions and Observations

Ortega, P., & Braun, D. (2012). Adaptive Coding of Actions and Observations. In NIPS Workshop on Information in Perception and Action 2012 (pp. 1-4).

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-B54A-B Version Permalink: https://hdl.handle.net/21.11116/0000-0001-8AC0-A
Genre: Conference Paper

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 Creators:
Ortega, PA1, Author           
Braun, DA1, Author           
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1Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: The application of expected utility theory to construct adaptive agents is both computationally intractable and statistically questionable. To overcome these difficulties, agents need the ability to delay the choice of the optimal policy to a later stage when they have learned more about the environment. How should agents do this optimally? An information-theoretic answer to this question is given by the Bayesian control rule—the solution to the adaptive coding problem when there are not only observations but also actions. This paper reviews the central ideas behind the Bayesian control rule.

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 Dates: 2012-12
 Publication Status: Issued
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 Identifiers: BibTex Citekey: OrtegaB2012
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Title: NIPS Workshop on Information in Perception and Action 2012
Place of Event: Lake Tahoe, NV, USA
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Title: NIPS Workshop on Information in Perception and Action 2012
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 4 Identifier: -