Abstract

We consider the following frustrated optimization problem: given a prior probability distribution qq, find the distribution pp minimizing the relative entropy with respect to qq such that mean(p)\textrm{mean}(p) is fixed and large. We show that solutions to this problem are asymptotically Gaussian. As an application we derive an HH-type theorem for evolutionary dynamics: the entropy of the (standardized) distribution of fitness of a population evolving under natural selection is eventually increasing.

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