We consider the following frustrated optimization problem: given a prior probability distribution $q$, find the distribution $p$ minimizing the relative entropy with respect to $q$ such that $\textrm{ mean}(p)$ is fixed and large. We show that solutions to this problem are asymptotically Gaussian. As an application we derive an $H$-type theorem for evolutionary dynamics: the entropy of the (standardized) distribution of fitness of a population evolving under natural selection is eventually increasing.
Categories: cond-mat.stat-mech math.PR math.ST q-bio.PE stat.TH