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Mean-Variance Tradeoffs in an Undiscounted MDP: The Unichain Case

Author

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  • Kun-Jen Chung

    (National Taiwan Institute of Technology, Taipei, Taiwan, Republic of China)

Abstract

The problem analyzed here is the computation of Pareto optima in the sense of high mean and low variance of the stationary distribution in the unichain, undiscounted Markov decision process (MDP, for short).

Suggested Citation

  • Kun-Jen Chung, 1994. "Mean-Variance Tradeoffs in an Undiscounted MDP: The Unichain Case," Operations Research, INFORMS, vol. 42(1), pages 184-188, February.
    • Handle: RePEc:inm:oropre:v:42:y:1994:i:1:p:184-188
    DOI: 10.1287/opre.42.1.184
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    Cited by:

    1. Li Xia, 2020. "Risk‐Sensitive Markov Decision Processes with Combined Metrics of Mean and Variance," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2808-2827, December.
    2. Alessandro Arlotto & Noah Gans & J. Michael Steele, 2014. "Markov Decision Problems Where Means Bound Variances," Operations Research, INFORMS, vol. 62(4), pages 864-875, August.
    3. Ma, Shuai & Ma, Xiaoteng & Xia, Li, 2023. "A unified algorithm framework for mean-variance optimization in discounted Markov decision processes," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1057-1067.

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