ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning
ME-IGM:最大熵多智能体强化学习中的个体-全局-最大
机构 * Carnegie Mellon University(卡内基梅隆大学) ; Zhejiang University(浙江大学) ; XPeng Inc.(XPeng公司) ; The University of Hong Kong(香港大学) ; INFIFORCE Intelligent Tech. Co., Ltd.(INFIFORCE智能科技有限公司)
AI总结 ME-IGM是一种结合最大熵探索与IGM条件的新型多智能体强化学习算法,通过解决局部策略与联合策略不一致问题,提升探索效率和性能。
Comments Published in the Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026)
Journal ref Proc. of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), Paphos, Cyprus, May 25 - 29, 2026, IFAAMAS, 19 pages