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Buletinul Academiei de Ştiinţe a Republicii Moldova. Matematica, 2018, Number 1, Pages 34–49
(Mi basm463)
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An approach for determining the optimal strategies for an average Markov decision problem with finite state and action spaces
Dmitrii Lozovanua, Stefan Picklb a Institute of Mathematics and Computer Science, 5 Academiei str., Chişinău, MD-2028 Moldova
b Institute for Theoretical Computer Science, Mathematics and Operations Research, Universität der Bundeswehr München, 85577 Neubiberg-München, Germany
Abstract:
The average reward Markov decision problem with finite state and action spaces is considered and an approach for determining the optimal pure and mixed stationary strategies for this problem is proposed. We show that the considered problem can be formulated in terms of stationary strategies where the objective function is quasi-monotonic (i.e. it is quasi-convex and quasi-concave) on the feasible set of stationary strategies. Using such a quasi-monotonic programming model with linear constraints we ground algorithms for determining the optimal pure and mixed stationary strategies for the average Markov decision problem.
Keywords and phrases:
Markov decision processes, average optimization criterion, stationary strategies, optimal strategies.
Received: 27.12.2017
Citation:
Dmitrii Lozovanu, Stefan Pickl, “An approach for determining the optimal strategies for an average Markov decision problem with finite state and action spaces”, Bul. Acad. Ştiinţe Repub. Mold. Mat., 2018, no. 1, 34–49
Linking options:
https://www.mathnet.ru/eng/basm463 https://www.mathnet.ru/eng/basm/y2018/i1/p34
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Abstract page: | 171 | Full-text PDF : | 47 | References: | 20 |
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