For decades, two-player (antagonistic) games on graphs have been a framework of choice for many important problems in theoretical computer science. A notorious one is controller synthesis, which can be rephrased through the game-theoretic metaphor as the quest for a winning strategy of the system in a game against its antagonistic environment. Depending on the specification, optimal strategies might be simple or quite complex, for example having to use (possibly infinite) memory. Hence, research strives to understand which settings allow for simple strategies. In 2005, Gimbert and Zielonka provided a complete characterization of preference relations (a formal framework to model specifications and game objectives) that admit memoryless optimal strategies for both players. In the last fifteen years however, practical applications have driven the community toward games with complex or multiple objectives, where memory -- finite or infinite -- is almost always required. Despite much effort, the exact frontiers of the class of preference relations that admit finite-memory optimal strategies still elude us. In this work, we establish a complete characterization of preference relations that admit optimal strategies using arena-independent finite memory, generalizing the work of Gimbert and Zielonka to the finite-memory case. We also prove an equivalent to their celebrated corollary of great practical interest: if both players have optimal (arena-independent-)finite-memory strategies in all one-player games, then it is also the case in all two-player games. Finally, we pinpoint the boundaries of our results with regard to the literature: our work completely covers the case of arena-independent memory (e.g., multiple parity objectives, lower- and upper-bounded energy objectives), and paves the way to the arena-dependent case (e.g., multiple lower-bounded energy objectives).
翻译:数十年来, 图表上的双玩者( 幻想主义) 游戏一直是理论计算机科学中许多重要问题的选择框架。 一个臭名昭著的游戏是控制器合成, 它可以通过游戏理论隐喻重新表达, 以寻求系统在游戏中战胜其对抗敌对环境的游戏中获胜战略。 取决于规格, 最佳战略可能是简单或相当复杂的, 比如必须使用( 可能无限的) 记忆。 因此, 研究努力理解哪些环境允许简单策略。 2005年, Gimbert 和 Zieronka 提供了一种完全的偏好关系描述( 模型规格和游戏目的的正式框架 ), 允许两个玩家都接受不记忆的最佳战略。 然而, 在过去15年里, 实际应用将社区推向复杂或多重目标的游戏, 几乎总是需要记忆 -- -- 有限或无限的 -- 。 尽管我们付出了很大努力, 接受有限和最优等量的最佳战略的准确的界限仍然不为我们。 在这项工作中, 我们建立了完全的偏爱关系描述, 承认最优化的战略, 以舞台- 固定的多重记忆和游戏中的一种方式, 最优等量的游戏的结果, 也证明我们最优等量的游戏 。