Abstract：To cope with the situation that the centralized decision-making is difficult to be implemented due to impeded communication and other reasons in complex battlefield environment in the future, a distributed task assignment algorithm of operation system of systems（SoS）is proposed based on multi-agent deep reinforcement learning technology. This algorithm designs an independent policy network for each combat unit, and the centralized training and decentralized execution methods are utilized to train the policy network. The results show that each combat unit entities has certain self-coordination ability after being trained, and the combat units can still allocate the SoS tasks independently and effectively even in the absence of central command and control（C2）nodes.
林萌龙, 陈涛, 任棒棒, 张萌萌, 陈洪辉. 基于多智能体深度强化学习的体系任务分配方法[J]. 指挥与控制学报, 2023, 9(1): 93-102.
LIN Menglong, CHEN Tao, REN Bangbang, ZHANG Mengmeng, CHEN Honghui. Task Assignment Method of Operation System of Systems Based on Multi-agent Deep Reinforcement Learning. Journal of Command and Control, 2023, 9(1): 93-102.
2023, Vol. 9 
