Markov Decision Processes and Stochastic Games with Total Effective Payoff

Authors Endre Boros, Khaled Elbassioni, Vladimir Gurvich, Kazuhisa Makino

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Endre Boros
Khaled Elbassioni
Vladimir Gurvich
Kazuhisa Makino

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Endre Boros, Khaled Elbassioni, Vladimir Gurvich, and Kazuhisa Makino. Markov Decision Processes and Stochastic Games with Total Effective Payoff. In 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 30, pp. 103-115, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


We consider finite Markov decision processes (MDPs) with undiscounted total effective payoff. We show that there exist uniformly optimal pure stationary strategies that can be computed by solving a polynomial number of linear programs. We apply this result to two-player zero-sum stochastic games with perfect information and undiscounted total effective payoff, and derive the existence of a saddle point in uniformly optimal pure stationary strategies.
  • Markov decision processes
  • undiscounted stochastic games
  • linear programming
  • mean payoff
  • total payoff


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