Reduction of a Markov decision process with non-linear discounting to a stochastic game with standard total undiscounted criterion

Piunovskiy, Alexey ORCID: 0000-0002-9683-4856, Presman, Ernst, Zhang, Yi ORCID: 0000-0002-3200-6306 and Zheng, Xinran (2025) Reduction of a Markov decision process with non-linear discounting to a stochastic game with standard total undiscounted criterion Annals of Operations Research. pp. 1-19. ISSN 0254-5330, 1572-9338

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Abstract

Abstract We consider a Markov decision process (MDP), whose total discounted utility is aggregated recursively with a concave discount function that is not necessarily linear. The state and action spaces are Borel spaces, and the utility function is nonnegative. We show that it can be reduced to a turn-based stochastic game model with the total undiscounted utility. This reduction result is then applied to the MDP problem with recursively aggregated utility to be maximized or cost to be minimized.

Item Type:	Article
Uncontrolled Keywords:	4901 Applied Mathematics, 49 Mathematical Sciences
Divisions:	Faculty of Science & Engineering Faculty of Science & Engineering > School of Physical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	14 Mar 2025 11:48
Last Modified:	27 Dec 2025 04:07
DOI:	10.1007/s10479-025-06540-9
Open Access URL:	https://doi.org/10.1007/s10479-025-06540-9
Related Websites:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3190821
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