Average Reward Optimality in Semi-Markov Decision Processes with Costly Interventions

Result code in IS VaVaI
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Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Average Reward Optimality in Semi-Markov Decision Processes with Costly Interventions
Original language description
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.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 41st International Conference on Mathematical Methods in Econometrics
ISBN
978-80-11-04132-8
ISSN
2788-3965
e-ISSN
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Number of pages
6
Pages from-to
378-383
Publisher name
The Czech Society of Operations Research
Place of publication
Praha
Event location
Prague
Event date
Sep 13, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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