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cs.AI2026
Value-Guided Repulsion for Offline Reinforcement Learning
Yixue Hao, Jiahao Zhang, Jiesong Lian +5
Drifting models have emerged as a highly efficient and stable paradigm for policy design in offline reinforcement learning (RL). However, standard drift policies determine repulsio…
cs.AI2024
DCMAC: Demand-aware Customized Multi-Agent Communication via Upper Bound Training
Dongkun Huo, Huateng Zhang, Yixue Hao +4
Efficient communication can enhance the overall performance of collaborative multi-agent reinforcement learning. A common approach is to share observations through full communicati…