The solution of an undiscounted completely ergodic Markov decision process by successive approximation

In this paper we consider a completely ergodic Markov decision process with finite state and decision spaces using the average return per unit time criterion. An algorithm is derived which approximates the optimal solution. It will be shown that this algorithm is finite and supplies upper and lower bounds for the maximal average return and a near optimal policy with average return between these bounds