论文标题
数据驱动的抽象具有线性PETC系统的概率保证
Data-driven Abstractions with Probabilistic Guarantees for Linear PETC Systems
论文作者
论文摘要
我们采用场景方法来计算基于有限数量的样本，可能是由未知PETC系统产生的平均样本间时间（AIST）的近似正确（PAC）。我们将场景方法扩展到多类SVM算法，以便在混凝土，未知状态空间和样本间时间之间构造PAC图。然后，我们构建了一个应用$ \ ell $ complete关系的交通模型，并在基础图中查找最小和最大平均重量的循环：这些循环在AIST上提供了下层和上限。数值基准显示了我们方法的实际适用性，该方法与基于模型的最新工具进行了比较。
We employ the scenario approach to compute probably approximately correct (PAC) bounds on the average inter-sample time (AIST) generated by an unknown PETC system, based on a finite number of samples. We extend the scenario approach to multiclass SVM algorithms in order to construct a PAC map between the concrete, unknown state-space and the inter-sample times. We then build a traffic model applying an $\ell$-complete relation and find, in the underlying graph, the cycles of minimum and maximum average weight: these provide lower and upper bounds on the AIST. Numerical benchmarks show the practical applicability of our method, which is compared against model-based state-of-the-art tools.
