RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness

1 code implementation • 22 Jun 2023 • Nicholas H. Barbara, Max Revay, Ruigang Wang, Jing Cheng, Ian R. Manchester

Neural networks are typically sensitive to small input perturbations, leading to unexpected or brittle behaviour.

reinforcement-learning

Learning Over Contracting and Lipschitz Closed-Loops for Partially-Observed Nonlinear Systems (Extended Version)

1 code implementation • 12 Apr 2023 • Nicholas H. Barbara, Ruigang Wang, Ian R. Manchester

This paper presents a policy parameterization for learning-based control on nonlinear, partially-observed dynamical systems.

Learning over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System

no code implementations • 8 Dec 2021 • Ruigang Wang, Nicholas H. Barbara, Max Revay, Ian R. Manchester

This paper proposes a nonlinear policy architecture for control of partially-observed linear dynamical systems providing built-in closed-loop stability guarantees.

Reinforcement Learning (RL)