Cooperation is a widespread phenomenon in nature, from viruses, bacteria, and social amoebae to insect societies, social animals, and humans. It is also crucially important to enable agents to learn to cooperate in multi-agent environments for many applications, e.g., autonomous driving, multi-robot control, traffic light control, smart grid control, network optimization, etc. In this talk, I will focus on our latest studies for multi-agent cooperation via communication, joint policy learning, adaptive learning rates, etc.
About CIR2020: To boost the theoretical and technological innovation of artificial intelligence, promote academic exchanges and technological progress in fields related to crowd intelligence, AIRS is holding a series seminar named Crowd Intelligence Research Series Seminar, inviting 9 scholars and researchers from different universities and institutes to share their researches in the field of crowd intelligence.
Researcher of Department of Computer Science and Technology, Peking University