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Information-Theoretic Bounded Rationality and Optimality

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Braun,  DA
Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Sensorimotor Learning and Decision-making, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Ortega,  PA
Research Group Sensorimotor Learning and Decision-making, Max Planck Institute for Intelligent Systems, Max Planck Society;
Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Braun, D., & Ortega, P. (2014). Information-Theoretic Bounded Rationality and Optimality. Entropy, 16(8), 4662-4676. doi:10.3390/e16084662.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0027-7FEB-5
Zusammenfassung
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 ⁽\epsilon⁾-optimality models of bounded rational decision making, where the decision maker is satisfied with any action in an ⁽\epsilon⁾-neighborhood of the optimal utility. We find that the stochastic policies that optimize the free energy trade-off comply with the notion of ⁽\epsilon⁾-optimality. Moreover, this optimality criterion even holds when the environment is adversarial. We conclude that the study of bounded rationality based on ⁽\epsilon⁾-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.