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Abstract:
Perfectly rational decisionmakers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here, we propose a thermodynamically inspired formalization of bounded rational decisionmaking where information processing is modelled as state changes in thermodynamic systems that can be quantified by differences in free energy. By optimizing a free energy, bounded rational decisionmakers trade off expected utility gains and informationprocessing costs measured by the relative entropy. As a result, the bounded rational decisionmaking problem can be rephrased in terms of wellknown variational principles from statistical physics. In the limit when computational costs are ignored, the maximum expected utility principle is recovered. We discuss links to existing decisionmaking frameworks and applications to human decisionmaking experiments that are at odds with expected utility theory. Since most of the mathematical machinery can be borrowed from statistical physics, the main contribution is to reinterpret the formalism of thermodynamic freeenergy differences in terms of bounded rational decisionmaking and to discuss its relationship to human decisionmaking experiments.