Targeted multi-agent communication algorithm based on state control  

作　　者：Li-yang Zhao Tian-qing Chang Lei Zhang Jie Zhang Kai-xuan Chu De-peng Kong 

机构地区：[1]Department of Weaponry and Control,Army Academy of Armored Forces,Beijing,100072,China [2]Unit 92942,Beijing,100161,China

出　　处：《Defence Technology（防务技术）》2024年第1期544-556,共13页Defence Technology

摘　　要：As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.

关 键 词：Multi-agent deep reinforcement learning State control Targeted interaction Communication mechanism 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP13[自动化与计算机技术—控制科学与工程]