Original title: Average Reward Optimality in Semi-Markov Decision Processes with Costly Interventions
Authors: Sladký, Karel
Document type: Papers
Conference/Event: MME 2023: Mathematical Methods in Economics /41./, Prague (CZ), 20230913
Year: 2023
Language: eng
Abstract: In this note we consider semi-Markov reward decision processes evolving on finite state spaces. We focus attention on average reward models, i.e. we establish explicit formulas for the growth rate of the total expected reward. In contrast to the standard models we assume that the decision maker can also change the running process by some (costly) intervention. Recall that the result for optimality criteria for the classical Markov decision chains in discrete and continuous time setting turn out to be a very specific case of the considered model. The aim is to formulate optimality conditions for semi-Markov models with interventions and present algorithmical procedures for finding optimal solutions.
Keywords: controlled semi-Markov reward processes; intervention of the decision maker; long-run optimality
Host item entry: Proceedings of the 41st International Conference on Mathematical Methods in Econometrics, ISBN 978-80-11-04132-8, ISSN 2788-3965

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2023/E/sladky-0583563.pdf
Original record: https://hdl.handle.net/11104/0351597

Permalink: http://www.nusl.cz/ntk/nusl-541551


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