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Dynamic principal agent model based on CMDP

Author

Listed:
  • Yuanyao Ding
  • Rangcheng Jia
  • Shaoxiang Tang

Abstract

Dynamic principal agent models are formulated based on constrained Markov decision process (CMDP), in which conditions are given that the state space of the system is countable and the agent chooses his actions from a countable action set. If the principal has finite alternative contracts to select, it is shown that the optimal contract solution and the corresponding optimal policy can be obtained by linear programming under the discounted criterion and average criterion. Copyright Springer-Verlag 2003

Suggested Citation

  • Yuanyao Ding & Rangcheng Jia & Shaoxiang Tang, 2003. "Dynamic principal agent model based on CMDP," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 58(1), pages 149-157, September.
    • Handle: RePEc:spr:mathme:v:58:y:2003:i:1:p:149-157
    DOI: 10.1007/s001860300276
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    Citations

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    Cited by:

    1. Hao Zhang & Stefanos Zenios, 2008. "A Dynamic Principal-Agent Model with Hidden Information: Sequential Optimality Through Truthful State Revelation," Operations Research, INFORMS, vol. 56(3), pages 681-696, June.
    2. Shuo Zeng & Moshe Dror, 2019. "Serving many masters: an agent and his principals," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 90(1), pages 23-59, August.
    3. Soroush Saghafian & Xiuli Chao, 2014. "The impact of operational decisions on the design of salesforce incentives," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(4), pages 320-340, June.
    4. Armando Mendoza-Pérez & Onésimo Hernández-Lerma, 2010. "Markov control processes with pathwise constraints," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(3), pages 477-502, June.
    5. Armando F. Mendoza-Pérez & Héctor Jasso-Fuentes & Omar A. De-la-Cruz Courtois, 2016. "Constrained Markov decision processes in Borel spaces: from discounted to average optimality," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 84(3), pages 489-525, December.

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