Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes

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Authors

BROŽEK Václav BRÁZDIL Tomáš CHATTERJEE Krishnendu FOREJT Vojtěch KUČERA Antonín

Year of publication 2011
Type Article in Proceedings
Conference Proceedings 26th Annual IEEE Symposium on Logic in Computer Science
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1109/LICS.2011.10
Field Informatics
Keywords Markov decision process; optimization with multiple objectives; mean payoff; Pareto curve; approximation
Description We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k reward functions, in the expectation objective the goal is to maximize the expected value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector.
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