Pareto curves of multidimensional Mean-Payoff games

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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 Σ2P 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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APA

Brenguier, R., & Raskin, J. F. (2015). Pareto curves of multidimensional Mean-Payoff games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9207, pp. 251–267). Springer Verlag. https://doi.org/10.1007/978-3-319-21668-3_15

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