This work concerns finte-state Markov decision chains endowed with the long-run average reward criterion. Assuming that the optimality equation has a solution, it is shown that a nearly optimal stationary policy, as well as an approximation to the optimal average reward within a specified error,...

This work concerns finte-state Markov decision chains endowed with the long-run average reward criterion. Assuming that the optimality equation has a solution, it is shown that a nearly optimal stationary policy, as well as an approximation to the optimal average reward within a specified error,...

We study controlled Markov chains with denumerable state space and bounded costs per stage. A (long-run) risk-sensitive average cost criterion, associated to an exponential utility function with a constant risk sensitivity coefficient, is used as a performance measure. The main assumption on the...