DELICIODeep Learning for Intelligent Cooperative Systems

We propose to combine machine learning and control theory for sequential decision-making of multiple agents. The project proposes fundamental contributions: adding stability to the algorithms of reinforcement learning; data driven methods for robust control; hybrid ML / CT methods for multi-horizon control and planning; decentralized control. The methodological contributions of this fundamental AI project will be applied to the robust control of UAV fleets.