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Synthesizing optimally resilient controllers
Acta Informatica ( IF 0.4 ) Pub Date : 2019-10-31 , DOI: 10.1007/s00236-019-00345-7
Daniel Neider , Alexander Weinert , Martin Zimmermann

Recently, Dallal, Neider, and Tabuada studied a generalization of the classical game-theoretic model used in program synthesis, which additionally accounts for unmodeled intermittent disturbances. In this extended framework, one is interested in computing optimally resilient strategies, i.e., strategies that are resilient against as many disturbances as possible. Dallal, Neider, and Tabuada showed how to compute such strategies for safety specifications. In this work, we compute optimally resilient strategies for a much wider range of winning conditions and show that they do not require more memory than winning strategies in the classical model. Our algorithms only have a polynomial overhead in comparison to the ones computing winning strategies. In particular, for parity conditions, optimally resilient strategies are positional and can be computed in quasipolynomial time.

中文翻译:

综合最佳弹性控制器

最近,Dallal、Neider 和 Tabuada 研究了程序综合中使用的经典博弈论模型的泛化,该模型另外解释了未建模的间歇性干扰。在这个扩展框架中,人们对计算最佳弹性策略感兴趣,即对尽可能多的干扰具有弹性的策略。Dallal、Neider 和 Tabuada 展示了如何为安全规范计算此类策略。在这项工作中,我们为更广泛的获胜条件计算了最佳弹性策略,并表明它们不需要比经典模型中的获胜策略更多的内存。与计算获胜策略的算法相比,我们的算法只有多项式开销。特别是,对于奇偶条件,
更新日期:2019-10-31
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