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, z6首页 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.
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Zongqing Lu
Researcher of Department of Computer Science and Technology, Peking University
卢宗青，，，， ，， ，北京大学推算机系助理教授、人为智能钻研院钻研员、博士生导师、“决策智能”课题组掌管人，，，， ，， ，入选国度海表高档次人才青年项目、北京大学博雅青年学者 。 。。。。 。重要钻研方向为（多智能体）强化进建 。 。。。。 。担任NeurIPS、 ICLR、CoRL、IJCAI、AAMAS、INFOCOM等会议TPC，，，， ，， ，Nature Machine Intelligence等审稿人 。 。。。。 。
CIR2020回首 | 卢宗青教授：Cooperative Multi-Agent Reinforcement Learning
