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• W2947183726 abstract "We consider the linear programming approach for constrained and unconstrained Markov decision processes (MDPs) under the long-run average-cost criterion, where the class of MDPs in our study have Borel state spaces and discrete countable action spaces. Under a strict unboundedness condition on the one-stage costs and a recently introduced majorization condition on the state transition stochastic kernel, we study infinite-dimensional linear programs for the average-cost MDPs and prove the absence of a duality gap and other optimality results. Our results do not require a lower-semicontinuous MDP model. Thus, they can be applied to countable action space MDPs where the dynamics and one-stage costs are discontinuous in the state variable. Our proofs make use of the continuity property of Borel measurable functions asserted by Lusin’s theorem." @default.
• W2947183726 created "2019-06-07" @default.
• W2947183726 creator A5014937312 @default.
• W2947183726 date "2022-05-01" @default.
• W2947183726 modified "2023-10-02" @default.
• W2947183726 title "On Linear Programming for Constrained and Unconstrained Average-Cost Markov Decision Processes with Countable Action Spaces and Strictly Unbounded Costs" @default.
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• W2947183726 doi "https://doi.org/10.1287/moor.2021.1177" @default.
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