New Algorithms for Combinations of Objectives using Separating Automata

Ashwani Anand, Nathanaël Fijalkow, Ali'enor Goubault-Larrecq, Jérôme Leroux, Pierre Ohlmann
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Abstract

The notion of separating automata was introduced by Bojanczyk and Czerwinski for understanding the first quasipolynomial time algorithm for parity games. In this paper we show that separating automata is a powerful tool for constructing algorithms solving games with combinations of objectives. We construct two new algorithms: the first for disjunctions of parity and mean payoff objectives, matching the best known complexity, and the second for disjunctions of mean payoff objectives, improving on the state of the art. In both cases the algorithms are obtained through the construction of small separating automata, using as black boxes the existing constructions for parity objectives and for mean payoff objectives.
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基于分离自动机的目标组合新算法
分离自动机的概念是由Bojanczyk和Czerwinski为理解奇偶对策的第一个拟多项式时间算法而引入的。在本文中,我们证明了分离自动机是构建求解具有目标组合的博弈的算法的强大工具。我们构建了两种新算法:第一种算法用于奇偶性和平均收益目标的析取,匹配最著名的复杂性;第二种算法用于平均收益目标的析取,改进了目前的技术水平。在这两种情况下,算法都是通过构建小型分离自动机获得的,使用现有的宇称目标和平均收益目标的结构作为黑盒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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