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We aim to build multi-agent systems for the real world.
To do so, we study (i) algorithmic foundations (reinforcement learning, control, game theory), (ii) applications to real-world systems (robotics), and (iii) how to make such systems trustworthy (scalable, robust, safe, fair).
See Publications for more details.
We are not limited to this. We are always open to interesting problems.