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On the policy improvement algorithm for ergodic risk-sensitive control

Published 10 Dec 2019 in math.OC and math.PR | (1912.04568v3)

Abstract: In this article we consider the ergodic risk-sensitive control problem for a large class of multidimensional controlled diffusions on the whole space. We study the minimization and maximization problems under either a blanket stability hypothesis, or a near-monotone assumption on the running cost. We establish the convergence of the policy improvement algorithm for these models. We also present a more general result concerning the region of attraction of the equilibrium of the algorithm.

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