Stochastic Control System

Stochastic control systems research focuses on designing and verifying controllers for systems exhibiting inherent randomness. Current efforts concentrate on developing methods to learn and certify the stability and safety of neural network-based controllers, often employing techniques like supermartingales to provide formal guarantees on system behavior. This research is crucial for deploying AI-based controllers in safety-critical applications, addressing the challenge of ensuring reliable performance in uncertain environments. The development of robust verification frameworks and efficient learning algorithms is driving progress in this field.