Nonstationary denumerable state Markov decision processes – with average variance criterion

Xianping Guo

Mathematical Methods of Operations Research, 1999, vol. 49, issue 1, 87-96

Abstract: . In this paper, we consider the nonstationary Markov decision processes (MDP, for short) with average variance criterion on a countable state space, finite action spaces and bounded one-step rewards. From the optimality equations which are provided in this paper, we translate the average variance criterion into a new average expected cost criterion. Then we prove that there exists a Markov policy, which is optimal in an original average expected reward criterion, that minimizies the average variance in the class of optimal policies for the original average expected reward criterion. Copyright Springer-Verlag Berlin Heidelberg 1999

Keywords: Key words: Discrete; time Markov decision processes; average expected criteria; optimality equations; average variance criterion; optimal Markov policies (search for similar items in EconPapers)
Date: 1999
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:49:y:1999:i:1:p:87-96

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DOI: 10.1007/PL00020908

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