Semi-infinite discounted Markov decision processes: Policy improvement and singular perturbations

Mohammed Abbad and Khalid Rahhali

Mathematical Methods of Operations Research, 2001, vol. 54, issue 2, 279-290

Abstract: In this paper, Discounted Markov Decision Processes with finite state and countable action set (semi-infinite DMDP for short) are considered. A policy improvement finite algorithm which finds a nearly optimal deterministic strategy is presented. The steps of the algorithm are based on the classical policy improvement algorithm for finite DMDPs. Singularly perturbed semi-infinite DMDPs are investigated. In case of perturbations, some sufficient condition is given to guarantee that there exists a nearly optimal deterministic strategy which can approximate nearly optimal strategies for a whole family of singularly perturbed semi-infinite DMDP. Copyright Springer-Verlag Berlin Heidelberg 2001

Keywords: Key words: Semi-infinite Markov decision processes; policy improvement; singular perturbation (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1007/s001860100143

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