This paper offers a data-driven divide-and-conquer strategy to analyze large-scale
interconnected networks, characterized by both unknown mathematical models and …

We introduce a novel approach for the construction of symbolic abstractions-simpler, finite-
state models-which mimic the behaviour of a system of interest, and are commonly utilized to …

We propose a sample-based, sequential method to abstract a (potentially black-box)
dynamical system with a sequence of memory-dependent Markov chains of increasing size …

Finite-state abstractions (aka symbolic models) present a promising avenue for the formal
verification and synthesis of controllers in continuous-space control systems. These …

Finite abstractions (aka symbolic models) offer an effective scheme for approximating the
complex continuous-space systems with simpler models in the discrete-space domain. A …

In this paper, we consider the problem of computing from data guaranteed set-valued over-
approximations of unknown monotone functions with additive disturbances. We provide a …

At the intersection of dynamical systems, control theory, and formal methods lies the
construction of symbolic abstractions: these typically represent simpler, finite-state models …

Symbolic control allows to provide formal guarantees for generic optimal control problems
on nonlinear systems. It relies on the construction of a finite abstraction of the system which …

This paper develops a physics-informed scenario approach for safety verification of
nonlinear systems using barrier certificates (BCs) to ensure that system trajectories remain …

The abstraction of dynamical systems is a powerful tool that enables the design of feedback
controllers using a correct-by-design framework. We investigate a novel scheme to obtain …