Non-randomized policies for constrained Markov decision processes

Richard Chen () and Eugene Feinberg

Mathematical Methods of Operations Research, 2007, vol. 66, issue 1, 165-179

Abstract: This paper addresses constrained Markov decision processes, with expected discounted total cost criteria, which are controlled by non-randomized policies. A dynamic programming approach is used to construct optimal policies. The convergence of the series of finite horizon value functions to the infinite horizon value function is also shown. A simple example illustrating an application is presented. Copyright Springer-Verlag 2007

Keywords: Constrained Markov; Decision processes; Dynamic programming; Non-randomized policies (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s00186-006-0133-x

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