Existence of optimal stationary policies in average reward Markov decision processes with a recurrent state

DOI10.1007/BF01189029zbMath0766.90083OpenAlexW2056748608MaRDI QIDQ1194211

Rolando Cavazos-Cadena

Publication date: 27 September 1992

Published in: Applied Mathematics and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01189029

zbMATH Keywords

renewal theoryrecurrent statecountable state spacediscrete time average reward Markov decision processesexistence of an optimal stationary policy

Mathematics Subject Classification ID

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

Related Items (6)

Necessary and sufficient conditions for a bounded solution to the optimality equation in average reward Markov decision chains ⋮ Conditions for existence of average and Blackwell optimal stationary policies in denumerable Markov decision processes ⋮ A note on the vanishing interest rate approach in average Markov decision chains with continuous and bounded costs ⋮ Equivalence of Lyapunov stability criteria in a class of Markov decision processes ⋮ Denumerable controlled Markov chains with average reward criterion: Sample path optimality ⋮ Denumerable state nonhomogeneous Markov decision processes

Cites Work

• A new condition for the existence of optimal stationary policies in average cost Markov decision processes
• Necessary and sufficient conditions for a bounded solution to the optimality equation in average reward Markov decision chains
• Necessary conditions for the optimality equation in average-reward Markov decision processes
• Conditions for the equivalence of optimality criteria in dynamic programming
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