Constrained Markov Decision Processes with Non-constant Discount Factor

Author:

Jasso-Fuentes HéctorORCID,Prieto-Rumeau TomásORCID

Abstract

AbstractThis paper studies constrained Markov decision processes under the total expected discounted cost optimality criterion, with a state-action dependent discount factor that may take any value between zero and one. Both the state and the action space are assumed to be Borel spaces. By using the linear programming approach, consisting in stating the control problem as a linear problem on a set of occupation measures, we show the existence of an optimal stationary Markov policy. Our results are based on the study of both weak-strong topologies in the space of occupation measures and Young measures in the space of Markov policies.

Funder

Ministerio de Ciencia e Innovación

Consejo Nacional de Ciencia y Tecnología

Publisher

Springer Science and Business Media LLC

Reference38 articles.

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