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 is concerned with develo** an open-source software tool, called IMPaCT, for
the parallelized verification and controller synthesis of large-scale stochastic systems using …

We consider the problem of learning control policies in discrete-time stochastic systems
which guarantee that the system stabilizes within some specified stabilization region with …

This paper addresses the problem of data-driven computation of controllers that are correct
by design for safetycritical systems and can provably satisfy (complex) functional …

This paper addresses the problem of data-driven computation of controllers that are correct
by design for safety-critical systems and can provably satisfy (complex) functional …

This paper introduces a novel abstraction-based framework for controller synthesis of
nonlinear discrete-time stochastic systems. The focus is on probabilistic reach-avoid …

The automated synthesis of control policies for stochastic dynamical systems presents
significant challenges. A standard approach is to construct a finite-state abstraction of the …

Designing controllers to satisfy temporal requirements has proven to be challenging for
dynamical systems that are affected by uncertainty. This is mainly due to the states evolving …

In this paper, we present a novel data-driven approach to quantify safety for non-linear,
discrete-time stochastic systems with unknown noise distribution. We define safety as the …

Grain drying environmental parameters are an important issue throughout the paddy grain
production process. A real-time monitoring system requires rapid, online, and accurate …