Approximation of average cost optimal policies for general Markov decision processes with unbounded costs

Evgueni Gordienko, Raúl Montes- De-Oca and Adolfo Minjárez-Sosa

Mathematical Methods of Operations Research, 1997, vol. 45, issue 2, 245-263

Abstract: The aim of the paper is to show that Lyapunov-like ergodicity conditions on Markov decision processes with Borel state space and possibly unbounded cost provide the approximation of an average cost optimal policy by solvingn-stage optimization problems (n=1, 2, ...). The used approach ensures the exponential rate of convergence. The approximation of this type would be useful to find adaptive procedures of control and to estimate stability of an optimal control under disturbances of the transition probability. Copyright Physica-Verlag 1997

Keywords: Markov Decision Process; Average Cost Criterion; Value Iteration; Approximation of Optimal Policy; Geometrical Convergence (search for similar items in EconPapers)
Date: 1997
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DOI: 10.1007/BF01193864

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