| Mean field multi-agent reinforcement learning Y Yang, R Luo, M Li, M Zhou, W Zhang, J Wang ICML 2018, Long Talk, 5571-5580, 2018 | 618 | 2018 |
| Multiagent bidirectionally-coordinated nets: Emergence of human-level coordination in learning to play starcraft combat games P Peng, Y Wen, Y Yang, Q Yuan, Z Tang, H Long, J Wang NeurIPS 2017 Workshop: Emergent Communication, 2017 | 511 | 2017 |
| Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning M Li, Y Jiao, T Qin, Y Yang, Z Gong, J Wang, C Wang, G Wu, J Ye WWW 2019 (oral), 2019 | 231 | 2019 |
| An Overview of Multi-Agent Reinforcement Learning from Game Theoretical Perspective Y Yang, J Wang arXiv preprint arXiv:2011.00583, 2020 | 179 | 2020 |
| Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning Y Wen, Y Yang, R Luo, J Wang, W Pan ICLR 2019, 2019 | 134 | 2019 |
| SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving M Zhou, J Luo, J Villela, Y Yang, D Rusu, J Miao, W Zhang, M Alban, ... Conference on Robotic Learning 2020 (Best System Paper Award), 2020 | 124 | 2020 |
| Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting Y Yang, A Kolesnikova, S Lessmann, T Ma, MC Sung, JEV Johnson European Journal of Operational Research, 2018 | 87* | 2018 |
| Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning JG Kuba, R Chen, M Wen, Y Wen, F Sun, J Wang, Y Yang ICLR 2022, 2021 | 82 | 2021 |
| Bi-level Actor-Critic for Multi-agent Coordination H Zhang, W Chen, Z Huang, M Li, Y Yang, W Zhang, J Wang AAAI 2020, 2019 | 65 | 2019 |
| A Review of Safe Reinforcement Learning: Methods, Theory and Applications S Gu, L Yang, Y Du, G Chen, F Walter, J Wang, Y Yang, A Knoll arXiv preprint arXiv:2205.10330, 2022 | 63 | 2022 |
| Multi-Agent Determinantal Q-Learning Y Yang, Y Wen, L Chen, J Wang, K Shao, D Mguni, W Zhang ICML 2020, 2020 | 63 | 2020 |
| Factorized Q-learning for large-scale multi-agent systems M Zhou, Y Chen, Y Wen, Y Yang, Y Su, W Zhang, D Zhang, J Wang International Conference on Distributed Artificial Intelligence, 1-7, 2019 | 61 | 2019 |
| Modelling Behavioural Diversity for Learning in Open-Ended Games NP Nieves, Y Yang, O Slumbers, DH Mguni, J Wang ICML 2021, Long Oral, 2021 | 48* | 2021 |
| Modelling Bounded Rationality in Multi-Agent Interactions by Generalized Recursive Reasoning Y Wen, Y Yang, R Luo, J Wang IJCAI 2020, 2019 | 45* | 2019 |
| Learning in Nonzero-Sum Stochastic Games with Potentials D Mguni, Y Wu, Y Du, Y Yang, Z Wang, M Li, Y Wen, J Jennings, J Wang ICML 2021, 2021 | 44* | 2021 |
| Offline pre-trained multi-agent decision transformer: One big sequence model tackles all smac tasks L Meng, M Wen, Y Yang, C Le, X Li, W Zhang, Y Wen, H Zhang, J Wang, ... arXiv preprint arXiv:2112.02845, 2021 | 41 | 2021 |
| A study of AI population dynamics with million-agent reinforcement learning Y Yang, L Yu, Y Bai, J Wang, W Zhang, Y Wen, Y Yu AAMAS 2018, 2017 | 41* | 2017 |
| Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games X Liu, H Jia, Y Wen, Y Yang, Y Hu, Y Chen, C Fan, Z Hu NeurIPS 2021, 2021 | 40* | 2021 |
| Multi-Agent Reinforcement Learning is a Sequence Modeling Problem M Wen, JG Kuba, R Lin, W Zhang, Y Wen, J Wang, Y Yang NeurIPS 2022, 2022 | 39 | 2022 |
| Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems Y Yang, J Luo, Y Wen, O Slumbers, D Graves, HB Ammar, J Wang, ... AAMAS 2021 (Best Blue Sky Paper Award), 2021 | 31 | 2021 |
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
