LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation

Guobin Zhu; Rui Zhou; Wenkang Ji; Shiyu Zhao

doi:10.1109/lra.2025.3577527

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JOURNAL ARTICLE

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation

Guobin Zhu Rui Zhou Wenkang Ji Shiyu Zhao

Year: 2025 Journal: IEEE Robotics and Automation Letters Vol: 10 (7)Pages: 7476-7483 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/lra.2025.3577527

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Keywords:

Reinforcement learning Computer science Reinforcement Artificial intelligence Materials science Composite material

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Reinforcement Learning in Robotics

Physical Sciences → Computer Science → Artificial Intelligence

Distributed Control Multi-Agent Systems

Physical Sciences → Computer Science → Computer Networks and Communications

Multi-Agent Systems and Negotiation

Physical Sciences → Computer Science → Artificial Intelligence

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation

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