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

Author

Listed:
  • Evgueni Gordienko
  • Raúl Montes-De-Oca
  • Adolfo Minjárez-Sosa

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

Suggested Citation

  • Evgueni Gordienko & Raúl Montes-De-Oca & Adolfo Minjárez-Sosa, 1997. "Approximation of average cost optimal policies for general Markov decision processes with unbounded costs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 45(2), pages 245-263, June.
    • Handle: RePEc:spr:mathme:v:45:y:1997:i:2:p:245-263
    DOI: 10.1007/BF01193864
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