Information-Theoretic Bounded Rationality for Learning and Decision-Making

Braun, D

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Information-Theoretic Bounded Rationality for Learning and Decision-Making

Braun, D. (2016). Information-Theoretic Bounded Rationality for Learning and Decision-Making. Talk presented at NIPS 2016 Workshop on Imperfect Decision Makers: Admitting Real-World Rationality. Barcelona, Spain.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0000-7BEB-E Version Permalink: https://hdl.handle.net/21.11116/0000-0000-C88A-3

Genre: Talk

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Braun, D^{1, 2, 3}, Author

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1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794
2Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497809
3Research Group Sensorimotor Learning and Decision-making, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1688138

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Abstract: We study an information-theoretic framework of bounded rational decision-making that trades off utility maximization against information-processing costs. We apply the basic principle of this framework to perception-action systems and show how the formation of abstractions and decision-making hierarchies depends on information-processing costs.

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Dates: Date issued: 2016-12-09

Publication Status: Issued

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Identifiers: BibTex Citekey: Braun2016

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Title: NIPS 2016 Workshop on Imperfect Decision Makers: Admitting Real-World Rationality

Place of Event: Barcelona, Spain

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Invited: Yes

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