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Continuous-time Markov decision processes with risk-sensitive finite-horizon cost criterion

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  • Qingda Wei

    (Huaqiao University)

Abstract

This paper studies continuous-time Markov decision processes with a denumerable state space, a Borel action space, bounded cost rates and possibly unbounded transition rates under the risk-sensitive finite-horizon cost criterion. We give the suitable optimality conditions and establish the Feynman–Kac formula, via which the existence and uniqueness of the solution to the optimality equation and the existence of an optimal deterministic Markov policy are obtained. Moreover, employing a technique of the finite approximation and the optimality equation, we present an iteration method to compute approximately the optimal value and an optimal policy, and also give the corresponding error estimations. Finally, a controlled birth and death system is used to illustrate the main results.

Suggested Citation

  • Qingda Wei, 2016. "Continuous-time Markov decision processes with risk-sensitive finite-horizon cost criterion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 84(3), pages 461-487, December.
    • Handle: RePEc:spr:mathme:v:84:y:2016:i:3:d:10.1007_s00186-016-0550-4
    DOI: 10.1007/s00186-016-0550-4
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    References listed on IDEAS

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    1. Confortola, Fulvia & Fuhrman, Marco, 2014. "Backward stochastic differential equations associated to jump Markov processes and applications," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 289-316.
    2. van Dijk, Nico M., 1988. "On the finite horizon Bellman equation for controlled Markov jump models with unbounded characteristics: existence and approximation," Stochastic Processes and their Applications, Elsevier, vol. 28(1), pages 141-157, April.
    3. Guo, Xianping & Zhang, Wenzhao, 2014. "Convergence of controlled models and finite-state approximation for discounted continuous-time Markov decision processes with constraints," European Journal of Operational Research, Elsevier, vol. 238(2), pages 486-496.
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    Citations

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    Cited by:

    1. Wei, Qingda, 2019. "Nonzero-sum risk-sensitive finite-horizon continuous-time stochastic games," Statistics & Probability Letters, Elsevier, vol. 147(C), pages 96-104.
    2. Subrata Golui & Chandan Pal & Subhamay Saha, 2022. "Continuous-Time Zero-Sum Games for Markov Decision Processes with Discounted Risk-Sensitive Cost Criterion," Dynamic Games and Applications, Springer, vol. 12(2), pages 485-512, June.
    3. Xin Guo & Qiuli Liu & Yi Zhang, 2019. "Finite horizon risk-sensitive continuous-time Markov decision processes with unbounded transition and cost rates," 4OR, Springer, vol. 17(4), pages 427-442, December.
    4. Subrata Golui & Chandan Pal, 2022. "Risk-sensitive discounted cost criterion for continuous-time Markov decision processes on a general state space," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(2), pages 219-247, April.
    5. Qingda Wei & Xian Chen, 2023. "Continuous-Time Markov Decision Processes Under the Risk-Sensitive First Passage Discounted Cost Criterion," Journal of Optimization Theory and Applications, Springer, vol. 197(1), pages 309-333, April.

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