Air-M: A Visual Reality Many-Agent Reinforcement Learning Platform for Large-Scale Aerial Unmanned System. - Jiabin Lou; Wenjun Wu 001; Shuhao Liao; Rongye Shi (IROS, 2023)

Leveraging Partial Symmetry for Multi-Agent Reinforcement Learning. - Xin Yu 009; Rongye Shi; Pu Feng; Yongkai Tian; Simin Li; Shuhao Liao; Wenjun Wu 001 (AAAI, 2024)

Synaptic Weight Optimization for Oscillatory Neural Networks: A Multi-Agent RL Approach. - Shuhao Liao; Xuehong Liu; Wenjun Wu 001; Rongye Shi; Junyu Zhang; Haopeng Wang (ICA, 2024)

Bench-CoE: a Framework for Collaboration of Experts from Benchmark. - Yuanshuai Wang; Xingjian Zhang 007; Jinkun Zhao; Siwei Wen; Peilin Feng; Shuhao Liao; Lei Huang 015; Wenjun Wu (CoRR, 2024)

SIGMA: Sheaf-Informed Geometric Multi-Agent Pathfinding. - Shuhao Liao; Weihang Xia; Yuhong Cao; Weiheng Dai; Chengyang He; Wenjun Wu; Guillaume Sartoretti (CoRR, 2025)

HELM: Human-Preferred Exploration with Language Models. - Shuhao Liao; Xuxin Lv; Yuhong Cao; Jeric Lew; Wenjun Wu; Guillaume Sartoretti (CoRR, 2025)