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First Passage Optimality and Variance Minimisation of Markov Decision Processes with Varying Discount Factors
Journal of Applied Probability
This paper deals with the first passage optimality and variance minimisation problems of discrete-time Markov decision processes (MDPs) with varying discount factors and unbounded rewards/costs. First, under suitable conditions slightly weaker than those in the previous literature on the standard (infinite horizon) discounted MDPs, we establish the existence and characterisation of the first passage expected-optimal stationary policies. Second, to further distinguish the expected-optimaldoi:10.1239/jap/1437658608 fatcat:743sk7rysrerld3362bozuwphi