In recent years, formal methods have been extensively used in the design of autonomous
systems. By employing mathematically rigorous techniques, formal methods can provide …

This paper studies formal synthesis of controllers for continuous-space systems with
unknown dynamics to satisfy requirements expressed as linear temporal logic formulas …

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

This letter is concerned with a data-driven technique for constructing finite Markov decision
processes (MDPs) as finite abstractions of discrete-time stochastic control systems with …

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 …

In this letter, we propose a data-driven approach for the construction of finite abstractions
(aka, symbolic models) for discrete-time deterministic control systems with unknown …

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 …

We employ the scenario optimisation theory to compute a traffic abstraction, with probability
guarantees of correctness, of a PETC system with unknown dynamics from a finite number of …

A common technique to verify complex logic specifications for dynamical systems is the
construction of symbolic abstractions: simpler, finite-state models whose behaviour mimics …

Construction of finite-state abstractions (aka symbolic abstractions) is a promising approach
for formal verification and controller synthesis of complex systems. Finite-state abstractions …