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,...

This work concerns controlled Markov chains with denumerable state space and discrete time parameter. The reward function is assumed to be≤0 and the performance of a control policy is measured by the expected total-reward criterion. Within this context, sufficient conditions are given so that...

This work concerns controlled Markov chains with denumerable state space and discrete time parameter. The reward function is assumed to be≤0 and the performance of a control policy is measured by the expected total-reward criterion. Within this context, sufficient conditions are given so that...