This paper presents three conditions. Each of them guarantees the uniqueness of optimal policies of discounted Markov decision processes. The conditions presented here impose hypotheses specifically on the state space X, the action space A, the admissible action sets A(x),x∈X, the transition...

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...