Optimal Values of Multidimensional Mean-Payoff Games
Abstract
In this paper, we study the set of thresholds that the protagonist can force in a zero-sum two-player
multidimensional mean-payoff game. The set of maximal elements of such a set is called the Pareto curve, a
classical tool to analyze trade-offs. As thresholds are vectors of real numbers in multiple dimensions, there exist
usually an infinite number of such maximal elements. Our main results are as follow. First, we study the geometry
of this set and show that it is definable as a finite union of convex sets given by linear inequations. Second, we
provide a Σ2 P algorithm to decide if this set intersects a convex set defined by linear inequations, and we prove
the optimality of our algorithm by providing a matching complexity lower bound for the problem. Furthermore, we
show that, under natural assumptions, i.e. fixed number of dimensions and polynomially bounded weights in the
game, the problem can be solved in deterministic polynomial time. Finally, we show that the Pareto curve can be
effectively constructed, and under the former natural assumptions, this construction can be done in deterministic
polynomial time.
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