Stochastic hybrid systems have received significant attentions as a relevant modeling
framework describing many systems, from engineering to the life sciences: they enable the …

We present SySCoRe, a MATLAB toolbox that synthesizes controllers for stochastic
continuous-state systems to satisfy temporal logic specifications. Starting from a system …

Probabilistic guarantees of safety and performance are important in constrained dynamical
systems with stochastic uncertainty. We consider the stochastic reachability problem, which …

We present SOCKS, a data-driven stochastic optimal control toolbox based in kernel
methods. SOCKS is a collection of data-driven algorithms that compute approximate …

In this paper, we compute finite sample bounds for data-driven approximations of the
solution to stochastic reachability problems. Our approach uses a nonparametric technique …

This report presents the results of a friendly competition for formal verification and policy
synthesis of stochastic models. It also introduces new benchmarks within this category, and …

For the formal verification and design of control systems, abstractions with quantified
accuracy are crucial. This is especially the case when considering accurate deviation …

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 …

Smart grid control and management is a growing research area that affects the global goals
of net-zero emissions, increased renewable energy generation, and efficient energy …

This report presents the results of a friendly competition for formal verification and policy
synthesis of stochastic models. It also introduces new benchmarks and their properties …