Learning efficient multi-agent communication: An information bottleneck approach R Wang, X He, R Yu, W Qiu, B An, Z Rabinovich ICML, 9908-9918, 2020 | 92 | 2020 |
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents W Qiu, X Wang, R Yu, X He, R Wang, B An, S Obraztsova, Z Rabinovich NeurIPS 2021, 2021 | 47 | 2021 |
Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning W Xue, W Qiu, B An, Z Rabinovich, S Obraztsova, KY Chai AAMAS 2022, 1418–1426, 2021 | 30 | 2021 |
Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks. W Qiu, H Chen, B An IJCAI, 4568-4574, 2019 | 26 | 2019 |
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach H Chen, W Qiu, HC Ou, B An, M Tambe UAI 2021, 2021 | 21 | 2021 |
Towards skilled population curriculum for multi-agent reinforcement learning R Wang, L Zheng, W Qiu, B He, B An, Z Rabinovich, Y Hu, Y Chen, T Lv, ... arXiv preprint arXiv:2302.03429, 2023 | 6 | 2023 |
Off-Beat Multi-Agent Reinforcement Learning W Qiu, W Wang, R Wang, B An, Y Hu, S Obraztsova, Z Rabinovich, J Hao, ... AAMAS 2023 Extended Abstract, 2022 | 1 | 2022 |
RPM: Generalizable Multi-Agent Policies for Multi-Agent Reinforcement Learning W Qiu, X Ma, B An, S Obraztsova, S Yan, Z Xu ICLR 2023, 2022 | 1 | 2022 |
Multi-agent reinforcement learning for complex sequential decision-making W Qiu Nanyang Technological University, 2023 | | 2023 |
Complex Contagion Influence Maximization: A Reinforcement Learning Approach H Chen, B Wilder, W Qiu, B An, E Rice, M Tambe IJCAI 2023, 2023 | | 2023 |