In this work, we propose a data-driven approach to synthesize safety controllers for
continuous-time nonlinear polynomial-type systems with unknown dynamics. The proposed …

This article is concerned with a formal verification scheme for both discrete-and continuous-
time deterministic systems with unknown mathematical models. The main target is to verify …

This work develops a measurement-driven and model-based formal verification approach,
applicable to dynamical systems with partly unknown dynamics. We provide a new …

Cyber–physical systems usually have complex dynamics and are required to fulfill complex
tasks. In recent years, formal methods from Computer Science have been used by control …

This dissertation provides efficient (data-driven) techniques to design highly-reliable
stochastic hybrid systems with mathematical guarantees by bringing together …

Obtaining complete and accurate models for the formal verification of systems is often hard
or impossible. We present a data-based verification approach, for properties expressed in a …

We present a new method for statistical verification of quantitative properties over a partially
unknown system with actions, utilising a parameterised model (in this work, a parametric …

This work is concerned with a compositional data-driven approach for formal safety
verification of large-scale continuous-time dynamical systems with unknown models. The …

We consider systems under uncertainty whose dynamics are partially unknown. Our aim is
to study satisfaction of temporal properties by trajectories of such systems. We express these …

This work develops a measurement-driven and model-based formal verification approach,
applicable to systems with partly unknown dynamics. We provide a principled method …