首页|Targeted multi-agent communication algorithm based on state control
Targeted multi-agent communication algorithm based on state control
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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 multi-agent 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 StarCraft 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.
Multi-agent deep reinforcement learningState controlTargeted interactionCommunication mechanism
Li-yang Zhao、Tian-qing Chang、Lei Zhang、Jie Zhang、Kai-xuan Chu、De-peng Kong
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Department of Weaponry and Control,Army Academy of Armored Forces,Beijing,100072,China
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