Distributed Learning for Multi-agent Games: Theory and Algorithms
TAN Shaolin1 GU Haibo 1, 2, * LIU Kexin 1, 2
1. Zhongguancun Laboratory, Beijing 100094, China; 2. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Abstract：Autonomous intelligent decisio n-making is a core technique of future unmanned system development, and game-theoretic learning is one of the key methods to realize autonomous intelligent decision-making. The rapid development field of the distributed learning for multi-agent games is centered on, a systematic introduction of its basic problems, research background and significance is performed. Then, regarding to two typical classes of games, including continuous action space games and discrete action space games, the recent construction and convergence research progresses of the distributed game-theoretic learning algorithms are overviewed. Finally, several challenging problems to be broken through in the future game-theoretic learning field are pointed out.
谭少林，谷海波，刘克新. 多智能体博弈中的分布式学习： 原理与算法[J]. 指挥与控制学报, 2024, 10(2): 127-136.
TAN Shaolin, GU Haibo1, LIU Kexin. Distributed Learning for Multi-agent Games: Theory and Algorithms. Journal of Command and Control, 2024, 10(2): 127-136.
2024, Vol. 10 
