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  Bounded rationality, abstraction and hierarchical decision-making: an information-theoretic optimality principle

Genewein, T., Leibfried, F., Grau-Moya, J., & Braun, D. (2015). Bounded rationality, abstraction and hierarchical decision-making: an information-theoretic optimality principle. Frontiers in Robotics and AI, 2: 27. doi:10.3389/frobt.2015.00027.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-556D-7 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-556E-5
Genre: Journal Article

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 Creators:
Genewein, T1, 2, Author           
Leibfried, F1, 2, Author           
Grau-Moya, J1, 2, Author           
Braun, DA1, 2, Author           
Affiliations:
1Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Intelligent Systems, Max Planck Society, Heisenbergstr. 3 70569 Stuttgart , DE, ou_1688138              
2Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497809              

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Free keywords: Forschungsgruppe Braun
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 Dates: 2015-10
 Publication Status: Published online
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.3389/frobt.2015.00027
BibTex Citekey: GeneweinLGB2015
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Title: Frontiers in Robotics and AI
Source Genre: Journal
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Pages: 24 Volume / Issue: 2 Sequence Number: 27 Start / End Page: - Identifier: ISSN: 2296-9144