Systems Control and Multiagent Optimization Research
Our focus is on advancing fundamental understanding of multi-agent decision-making in uncertain and dynamic environments. Towards this vision, we develop game theory and mechanism design, reinforcement learning theory, stochastic and distributed control. Our theoretical work is motivated by applications ranging from transportation and renewable energy systems to robotics.
Please explore our publications to learn more, or check out the interview and video below:
“Science is an incredibly attractive career path”: — an interview on the motivation and vision behind our group.
A brief video showing our daily work.
Please explore our publications to learn more, or check out the interview and video below:
“Science is an incredibly attractive career path”: — an interview on the motivation and vision behind our group.
A brief video showing our daily work.
