Constrained markov decision processes with compact state and action spaces: the average case

DOI10.1080/02331930008844505zbMath0961.93059OpenAlexW2067029462MaRDI QIDQ4512756

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Publication date: 2000

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331930008844505

zbMATH Keywords

linear programmingMarkov decision processessaddle-point theoremLagrange functionDoeblin's conditionconstrained MDPs with average criteriaconstrained optimal pair

Mathematics Subject Classification ID

Optimal stochastic control (93E20) Markov and semi-Markov decision processes (90C40)

Related Items (7)

Approximate dynamic programming for stochastic linear control problems on compact state spaces ⋮ Constrained Continuous-Time Markov Control Processes with Discounted Criteria ⋮ Constrained Markov decision processes with first passage criteria ⋮ On Linear Programming for Constrained and Unconstrained Average-Cost Markov Decision Processes with Countable Action Spaces and Strictly Unbounded Costs ⋮ Optimal policies for constrained average-cost Markov decision processes ⋮ Discounted continuous-time constrained Markov decision processes in Polish spaces ⋮ Discounted Markov decision processes with utility constraints

Cites Work

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• Ergodic Control of Markov Chains with Constraints—the General Case
• Linear Programming and Average Optimality of Markov Control Processes on Borel Spaces—Unbounded Costs
• Linear programming formulation of MDPs in countable state space: The multichain case
• Discrete-Time Controlled Markov Processes with Average Cost Criterion: A Survey

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