Abstract
In Markov decision processes with randomized reward function, countable states and finite actions, this paper studies total variance of average rewards. The variance is represented explicitly in a different form from the deterministic reward case. By parallel arguments to the case, we show the existence of a stationary deterministic policy which is mean-variance optimal. The recurrent condition used in the existence theorem is examined.
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