Distributed Decision-Making and Learning Lab

Welcome to the Distributed Decision-Making and Learning Lab at UConn (D2L2)! We design, analyze, control, and verify networked autonomous systems. Our research lies at the intersection of control theory, graph theory, game theory, cyber-physical systems, and machine learning, with recent interests in the design of safe and resilient networked multi-agent systems. Using the link below you will find some recent research areas we're currently working on.

Our Research

• Hierarchical Resilient Architecture of Networked Cyber-Physical Systems Against Attacks
• Attack-Resilient Reinforcement Learning for Heterogeneous Multi-Agent Systems
• Resilient and Optimal Hierarchical Control of Clustered DC Microgrids against FDI Attacks

Learn More About Our Research

[Nov 23]: Shan Zuo is invited to serve on NSF CPS Panel.

[Nov 23]: Our paper "Resilient Containment Control of Heterogeneous Multi-Agent Systems Against Unbounded Attacks on Sensors and Actuators" is accepted for publication in the IEEE Transactions on Control of Network Systems.

[Oct 23]: Shan Zuo is invited to serve on NSF EPCN Panel.

[Oct 23]: Shan Zuo serves as the Associate Editor of Transactions of the Institute of Measurement and Control.

[Sep 23]: Shan Zuo serves as the Associate Editor of IEEE Transactions on Neural Networks and Learning Systems.

[Mar 23] : Mohamadamin Rajabinezhad is awarded the Next Gen scholar GE fellowship. The fellowship entails $7500 of support for one academic year.