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Trading Infinite Memory for Uniform Randomness in Timed Games

机译:为计时游戏中的均匀随机性交换无限内存

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We consider concurrent two-player timed automaton games with ω-regular objectives specified as parity conditions. These games offer an appropriate model for the synthesis of real-time controllers. Earlier works on timed games focused on pure strategies for each player. We study, for the first time, the use of randomized strategies in such games. While pure (i.e., nonrandomized) strategies in timed games require infinite memory for winning even with respect to reachability objectives, we show that randomized strategies can win with finite memory with respect to all parity objectives. Also, the synthesized randomized realtime controllers are much simpler in structure than the corresponding pure controllers, and therefore easier to implement. For safety objectives we prove the existence of pure finite-memory winning strategies. Finally, while randomization helps in simplifying the strategies required for winning timed parity games, we prove that randomization does not help in winning at more states.
机译:我们考虑并发两人定时自动机游戏,其中ω-常规目标指定为奇偶条件。这些游戏为实时控制器的综合提供了合适的模型。早期的定时游戏主要针对每个玩家制定纯粹的策略。我们首次研究了此类游戏中随机策略的使用。虽然计时游戏中的纯(即非随机)策略需要无限的记忆才能赢得甚至就可达成性目标而言,但我们证明了随机策略可以针对所有奇偶目标以有限的记忆取胜。而且,合成的随机实时控制器在结构上比相应的纯控制器要简单得多,因此易于实现。对于安全目标,我们证明了存在纯粹的有限内存获胜策略。最后,尽管随机化有助于简化赢得定时平价游戏所需的策略,但我们证明了随机化无助于赢得更多州。

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