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Markov Decision Processes with Exogenous Variables

Author

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  • Robert L. Bray

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208-0814)

Abstract

I present two algorithms for solving dynamic programs with exogenous variables: endogenous value iteration and endogenous policy iteration. These algorithms are always at least as fast as relative value iteration and relative policy iteration, and they are faster when the endogenous variables converge to their stationary distributions sooner than the exogenous variables.

Suggested Citation

  • Robert L. Bray, 2019. "Markov Decision Processes with Exogenous Variables," Management Science, INFORMS, vol. 65(10), pages 4598-4606, October.
    • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:10:p:4598-4606
    DOI: 10.1287/mnsc.2018.3158
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    References listed on IDEAS

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    1. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
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    6. Robert L. Bray, 2019. "Strong convergence and dynamic economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 43-65, January.
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    8. Daniel Adelman & Angelo J. Mancini, 2016. "Optimality of Quasi-Open-Loop Policies for Discounted Semi-Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1222-1247, November.
    9. Victor Aguirregabiria & Arvind Magesan, "undated". "Soultion and Estimation of Dynamic Discrete Choice Structural Models Using Euler Equations," Working Papers 2016-32, Department of Economics, University of Calgary, revised 24 May 2016.
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    Cited by:

    1. Ecenur Oguz & Robert L. Bray, 2026. "Training Neural Networks Embedded in Dynamic Discrete Choice Models," Papers 2604.09736, arXiv.org.
    2. David B. Brown & Jingwei Zhang, 2022. "Dynamic Programs with Shared Resources and Signals: Dynamic Fluid Policies and Asymptotic Optimality," Operations Research, INFORMS, vol. 70(5), pages 3015-3033, September.

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