A mean-variance optimization problem for discounted Markov decision processes

DOI10.1016/j.ejor.2012.01.051zbMath1253.90214OpenAlexW2014323878MaRDI QIDQ1926755

Liuer Ye, George Yin, Xianping Guo

Publication date: 29 December 2012

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2012.01.051

zbMATH Keywords

meanefficient frontiervariance criterionpolicy iteration algorithmdiscounted rewardfinite continuous-time mdps

Mathematics Subject Classification ID

Markov and semi-Markov decision processes (90C40)

Related Items (11)

Finite horizon continuous-time Markov decision processes with mean and variance criteria ⋮ Minimum Average Value-at-Risk for Finite Horizon Semi-Markov Decision Processes in Continuous Time ⋮ Optimization of Markov decision processes under the variance criterion ⋮ Mean-variance problems for finite horizon semi-Markov decision processes ⋮ First Passage Optimality and Variance Minimisation of Markov Decision Processes with Varying Discount Factors ⋮ A unified algorithm framework for mean-variance optimization in discounted Markov decision processes ⋮ Variance minimization of parameterized Markov decision processes ⋮ A Sensitivity‐Based Construction Approach to Variance Minimization of Markov Decision Processes ⋮ Mean-semivariance optimality for continuous-time Markov decision processes ⋮ On the First Passage $g$-Mean-Variance Optimality for Discounted Continuous-Time Markov Decision Processes ⋮ Algorithmic aspects of mean-variance optimization in Markov decision processes

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