| Counterfactual conservative Q learning for offline multi-agent reinforcement learning J Shao*, Y Qu*, C Chen, H Zhang, X Ji Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Complementary attention for multi-agent reinforcement learning J Shao, H Zhang, Y Qu, C Liu, S He, Y Jiang, X Ji International Conference on Machine Learning, 30776-30793, 2023 | 2 | 2023 |
| Hokoff: real game dataset from honor of kings and its offline reinforcement learning benchmarks Y Qu*, B Wang*, J Shao*, Y Jiang, C Chen, Z Ye, L Linc, Y Feng, L Lai, ... Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| LLM-Empowered State Representation for Reinforcement Learning B Wang*, Y Qu*, Y Jiang, J Shao, C Liu, W Yang, X Ji Forty-first International Conference on Machine Learning, 0 | | |
| HoK3v3: an Environment for Generalization in Heterogeneous Multi-agent Reinforcement Learning L Liu, J Shao, X Chen, Y Qu, B Wang, Z Ye, Y Tu, H Qin, YJ Feng, L Lai, ... | | |
Jianzhun ShaoTsinghua UniversityVerified email at mails.tsinghua.edu.cn
