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[BHM+17] Patricia Bouyer, Piotr Hofman, Nicolas Markey, Mickael Randour, and Martin Zimmermann. Bounding Average-energy Games. In FoSSaCS'17, Lecture Notes in Computer Science 10203, pages 179-195. Springer-Verlag, April 2017.
Abstract

We consider average-energy games, where the goal is to minimize the long-run average of the accumulated energy. Decidability of average-energy games with a lower-bound constraint on the energy level (but no upper bound) is an open problem; in particular, there is no known upper bound on the memory that is required for winning strategies.

By reducing average-energy games with lower-bounded energy to infinite-state mean-payoff games and analyzing the frequency of low-energy configurations, we show an almost tight doubly-exponential upper bound on the necessary memory, and that the winner of average-energy games with lower-bounded energy can be determined in doubly-exponential time. We also prove EXPSPACE-hardness of this problem.

Finally, we consider multi-dimensional extensions of all types of average-energy games: without bounds, with only a lower bound, and with both a lower and an upper bound on the energy. We show that the fully-bounded version is the only case to remain decidable in multiple dimensions.

@inproceedings{fossacs2017-BHMRZ,
  author =              {Bouyer, Patricia and Hofman, Piotr and Markey,
                         Nicolas and Randour, Mickael and Zimmermann, Martin},
  title =               {Bounding Average-energy Games},
  editor =              {Esparza, Javier and Murawski, Andrzej},
  booktitle =           {{P}roceedings of the 20th {I}nternational
                         {C}onference on {F}oundations of {S}oftware
                         {S}cience and {C}omputation {S}tructure
                         ({FoSSaCS}'17)},
  acronym =             {{FoSSaCS}'17},
  publisher =           {Springer-Verlag},
  series =              {Lecture Notes in Computer Science},
  volume =              {10203},
  pages =               {179-195},
  year =                {2017},
  month =               apr,
  doi =                 {10.1007/978-3-662-54458-7_11},
  abstract =            {We~consider average-energy games, where the goal is
                         to minimize the long-run average of the accumulated
                         energy. Decidability of average-energy games with a
                         lower-bound constraint on the energy level (but~no
                         upper bound) is an open problem; in~particular,
                         there is no known upper bound on the memory that is
                         required for winning strategies.\par By~reducing
                         average-energy games with lower-bounded energy to
                         infinite-state mean-payoff games and analyzing the
                         frequency of low-energy configurations, we~show an
                         almost tight doubly-exponential upper bound on the
                         necessary memory, and that the winner of
                         average-energy games with lower-bounded energy can
                         be determined in doubly-exponential time. We~also
                         prove EXPSPACE-hardness of this problem.\par
                         Finally, we~consider multi-dimensional extensions of
                         all types of average-energy games: without bounds,
                         with only a lower bound, and with both a lower and
                         an upper bound on the energy. We show that the
                         fully-bounded version is the only case to remain
                         decidable in multiple dimensions.},
}
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