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Entropy 2014, 16(8), 4662-4676; doi:10.3390/e16084662

Information-Theoretic Bounded Rationality and ε-Optimality

1
Max Planck Institute for Biological Cybernetics, Max Planck Institute for Intelligent Systems, Spemannstrasse 38, Tübingen 72076, Germany
2
GRASP Laboratory, Electrical and Systems Engineering Department, University of Pennsylvania, Philadelphia, PA 19104, USA
*
Authors to whom correspondence should be addressed.
Received: 19 July 2014 / Revised: 11 August 2014 / Accepted: 15 August 2014 / Published: 21 August 2014
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Abstract

Bounded rationality concerns the study of decision makers with limited information processing resources. Previously, the free energy difference functional has been suggested to model bounded rational decision making, as it provides a natural trade-off between an energy or utility function that is to be optimized and information processing costs that are measured by entropic search costs. The main question of this article is how the information-theoretic free energy model relates to simple ε-optimality models of bounded rational decision making, where the decision maker is satisfied with any action in an ε-neighborhood of the optimal utility. We find that the stochastic policies that optimize the free energy trade-off comply with the notion of ε-optimality. Moreover, this optimality criterion even holds when the environment is adversarial. We conclude that the study of bounded rationality based on ε-optimality criteria that abstract away from the particulars of the information processing constraints is compatible with the information-theoretic free energy model of bounded rationality. View Full-Text
Keywords: bounded rationality; ε-optimality; probabilistic choice; ambiguity bounded rationality; ε-optimality; probabilistic choice; ambiguity
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Braun, D.A.; Ortega, P.A. Information-Theoretic Bounded Rationality and ε-Optimality. Entropy 2014, 16, 4662-4676.

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