The complexity of multi-mean-payoff and multi-energy games

In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always nonnegative. Multi-mean-payoff and multi-energy games replace in...

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Vydáno v:Information and computation Ročník 241; s. 177 - 196
Hlavní autoři: Velner, Yaron, Chatterjee, Krishnendu, Doyen, Laurent, Henzinger, Thomas A., Rabinovich, Alexander, Raskin, Jean-François
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.04.2015
ISSN:0890-5401, 1090-2651
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Shrnutí:In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always nonnegative. Multi-mean-payoff and multi-energy games replace individual weights by tuples, and the limit average (resp., running sum) of each coordinate must be (resp., remain) nonnegative. We prove finite-memory determinacy of multi-energy games and show inter-reducibility of multi-mean-payoff and multi-energy games for finite-memory strategies. We improve the computational complexity for solving both classes with finite-memory strategies: we prove coNP-completeness improving the previous known EXPSPACE bound. For memoryless strategies, we show that deciding the existence of a winning strategy for the protagonist is NP-complete. We present the first solution of multi-mean-payoff games with infinite-memory strategies: we show that mean-payoff-sup objectives can be decided in NP∩coNP, whereas mean-payoff-inf objectives are coNP-complete.
ISSN:0890-5401
1090-2651
DOI:10.1016/j.ic.2015.03.001