Specification Mining and Robust Design under Uncertainty
Specification Mining and Robust Design under Uncertainty
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不确定性下的规范挖掘与鲁棒设计
DOI：
10.1145/3358231
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
P. Bogdan
中科院分区：
文献类型：
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作者：
Panagiotis Kyriakis;Jyotirmoy V. Deshmukh;P. Bogdan
在本文中，我们提出了随机时序逻辑(STTL)作为一种表示受控随机动力系统时变行为的概率规范的形式。为了使STTL成为一种更有效的规范形式化形式，我们引入了STTL的量化语义来推理给定系统对STTL规范的健壮性满足。此外，我们还提出以鲁棒性值作为目标函数，通过随机优化算法使其最大化，以达到控制器设计的目的。最后，我们提出了一种基于参数-STTL规范的参数推理算法，该算法允许从底层系统的输出轨迹挖掘规范。我们在两个受汽车领域启发的案例研究上演示和验证了我们的框架。
In this paper, we propose Stochastic Temporal Logic (StTL) as a formalism for expressing probabilistic specifications on time-varying behaviors of controlled stochastic dynamical systems. To make StTL a more effective specification formalism, we introduce the quantitative semantics for StTL to reason about the robust satisfaction of an StTL specification by a given system. Additionally, we propose using the robustness value as the objective function to be maximized by a stochastic optimization algorithm for the purpose of controller design. Finally, we formulate an algorithm for parameter inference for Parameteric-StTL specifications, which allows specifications to be mined from output traces of the underlying system. We demonstrate and validate our framework on two case studies inspired by the automotive domain.