Risk-sensitive control of Markov chains and differential games

Abstract

Considers the long-run average risk-sensitive optimal control problem for Markov chains on a countable state space. It is shown that the equivalence with stochastic differential games that had been previously established for stochastic dynamical systems holds for the average risk-sensitive optimal control problem for Markov chains as well. The approach is based on the Donsker-Varadhan large deviations theory. >