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Optimality equations and inequalities in a class of risk-sensitive average cost Markov decision chains

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  • Rolando Cavazos-Cadena

Abstract

This note concerns controlled Markov chains on a denumerable sate space. The performance of a control policy is measured by the risk-sensitive average criterion, and it is assumed that (a) the simultaneous Doeblin condition holds, and (b) the system is communicating under the action of each stationary policy. If the cost function is bounded below, it is established that the optimal average cost is characterized by an optimality inequality, and it is to shown that, even for bounded costs, such an inequality may be strict at every state. Also, for a nonnegative cost function with compact support, the existence an uniqueness of bounded solutions of the optimality equation is proved, and an example is provided to show that such a conclusion generally fails when the cost is negative at some state. Copyright Springer-Verlag 2010

Suggested Citation

  • Rolando Cavazos-Cadena, 2010. "Optimality equations and inequalities in a class of risk-sensitive average cost Markov decision chains," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(1), pages 47-84, February.
    • Handle: RePEc:spr:mathme:v:71:y:2010:i:1:p:47-84
    DOI: 10.1007/s00186-009-0285-6
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    References listed on IDEAS

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    1. Stratton C. Jaquette, 1976. "A Utility Criterion for Markov Decision Processes," Management Science, INFORMS, vol. 23(1), pages 43-49, September.
    2. Ronald A. Howard & James E. Matheson, 1972. "Risk-Sensitive Markov Decision Processes," Management Science, INFORMS, vol. 18(7), pages 356-369, March.
    3. Rolando Cavazos-Cadena & Emmanuel Fernández-Gaucherand, 1999. "Controlled Markov chains with risk-sensitive criteria: Average cost, optimality equations, and optimal solutions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 49(2), pages 299-324, April.
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    Cited by:

    1. Marcin Pitera & Mikl'os R'asonyi, 2023. "Utility-based acceptability indices," Papers 2310.02014, arXiv.org.
    2. Qingda Wei & Xian Chen, 2019. "Risk-Sensitive Average Equilibria for Discrete-Time Stochastic Games," Dynamic Games and Applications, Springer, vol. 9(2), pages 521-549, June.
    3. Qingda Wei & Xian Chen, 2021. "Nonzero-sum Risk-Sensitive Average Stochastic Games: The Case of Unbounded Costs," Dynamic Games and Applications, Springer, vol. 11(4), pages 835-862, December.
    4. Arapostathis, Ari & Biswas, Anup, 2018. "Infinite horizon risk-sensitive control of diffusions without any blanket stability assumptions," Stochastic Processes and their Applications, Elsevier, vol. 128(5), pages 1485-1524.

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