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Multiagent Reinforcement Learning With Heterogeneous Graph Attention Network

文献类型：期刊论文

作者Du, Wei2,3; Ding, Shifei2,3; Zhang, Chenglong2,3; Shi, Zhongzhi1
刊名IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
出版日期2022-11-04
页码10
关键词Reinforcement learning Multi-agent systems Aggregates Task analysis Scalability Marine vehicles Learning systems Graph attention network heterogeneous agents multiagent reinforcement learning (MARL) relationship-level attention
ISSN号2162-237X
DOI10.1109/TNNLS.2022.3215774
英文摘要Most recent research on multiagent reinforcement learning (MARL) has explored how to deploy cooperative policies for homogeneous agents. However, realistic multiagent environments may contain heterogeneous agents that have different attributes or tasks. The heterogeneity of the agents and the diversity of relationships cause the learning of policy excessively tough. To tackle this difficulty, we present a novel method that employs a heterogeneous graph attention network to model the relationships between heterogeneous agents. The proposed method can generate an integrated feature representation for each agent by hierarchically aggregating latent feature information of neighbor agents, with the importance of the agent level and the relationship level being entirely considered. The method is agnostic to specific MARL methods and can be flexibly integrated with diverse value decomposition methods. We conduct experiments in predator-prey and StarCraft Multiagent Challenge (SMAC) environments, and the empirical results demonstrate that the performance of our method is superior to existing methods in several heterogeneous scenarios.
资助项目National Natural Science Foundation of China[61976216] ; National Natural Science Foundation of China[62276265]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000881975400001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/19855]  
专题中国科学院计算技术研究所期刊论文
通讯作者Ding, Shifei
作者单位1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
2.China Univ Min & Technol, Minist Educ, Mine Digitizat Engn Res Ctr, Xuzhou 221116, Jiangsu, Peoples R China
3.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
推荐引用方式
GB/T 7714		 Du, Wei,Ding, Shifei,Zhang, Chenglong,et al. Multiagent Reinforcement Learning With Heterogeneous Graph Attention Network[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2022:10.
APA Du, Wei,Ding, Shifei,Zhang, Chenglong,&Shi, Zhongzhi.(2022).Multiagent Reinforcement Learning With Heterogeneous Graph Attention Network.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,10.
MLA Du, Wei,et al."Multiagent Reinforcement Learning With Heterogeneous Graph Attention Network".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022):10.

入库方式： OAI收割

来源：计算技术研究所

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