Xueguang Lyu (吕雪广) is a CS Ph.D. student at Khoury College of Computer Sciences of Northeastern University, advised by Christopher Amato. Xueguang’s research interests include reinforcement learning, artificial intelligence, and multi-agent system.
Xueguang is interested in enabling effective multi-agent exploration and cooperation in game-theoritic simulations as well as in real-world tasks. His recent work focuses on analyzing multi-agent actor-critic methods in centralized training settings, and utilizing centralized training to learn decentralized cooperating policies.
PhD in Computer Science, in progress
Northeastern University
MS in Computer Science, 2018
Northeastern University
BS in Informatics, 2016
University of California, Irvine