Empirical estimation in average Markov control processes

This work concerns discrete-time Markov control processes with unbounded costs and unknown disturbance distribution θ. Assuming observability of the random disturbance, we estimate θ using its empirical estimator, which, combined with a variant of the vanishing discount factor approach, yields average cost optimal policies.