| 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 | 851 | 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 | 626 | 2017 |
| Baichuan 2: Open Large-scale Language Models A Yang, B Xiao, B Wang, B Zhang, C Yin, C Lv, D Pan, D Wang, D Yan, ... arXiv preprint arXiv:2309.10305, 2023 | 577* | 2023 |
| An Overview of Multi-Agent Reinforcement Learning from Game Theoretical Perspective Y Yang, J Wang arXiv preprint arXiv:2011.00583, 2020 | 351 | 2020 |
| 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 | 318 | 2019 |
| Beavertails: Towards improved safety alignment of llm via a human-preference dataset J Ji, M Liu, J Dai, X Pan, C Zhang, C Bian, R Sun, Y Wang, Y Yang NeurIPS 2023, 2023 | 309 | 2023 |
| 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 | 299 | 2022 |
| 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 | 271 | 2021 |
| Safe RLHF: Safe Reinforcement Learning from Human Feedback J Dai, X Pan, R Sun, J Ji, X Xu, M Liu, Y Wang, Y Yang arXiv preprint arXiv:2310.12773, 2023 | 232 | 2023 |
| Ai alignment: A comprehensive survey J Ji, T Qiu, B Chen, B Zhang, H Lou, K Wang, Y Duan, Z He, J Zhou, ... arXiv preprint arXiv:2310.19852, 2023 | 227 | 2023 |
| 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 | 225* | 2020 |
| 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 | 200 | 2022 |
| Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning Y Wen, Y Yang, R Luo, J Wang, W Pan ICLR 2019, 2019 | 180 | 2019 |
| Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting A Kim, Y Yang, S Lessmann, T Ma, MC Sung, JEV Johnson European Journal of Operational Research 283 (1), 217-234, 2020 | 132 | 2020 |
| 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 | 105 | 2019 |
| Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning Y Chen, Y Yang, T Wu, S Wang, X Feng, J Jiang, SM McAleer, H Dong, ... NeurIPS 2022, 2022 | 104 | 2022 |
| Multi-Agent Determinantal Q-Learning Y Yang, Y Wen, L Chen, J Wang, K Shao, D Mguni, W Zhang ICML 2020, 2020 | 86 | 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 | 83 | 2019 |
| Jarvis-1: Open-world multi-task agents with memory-augmented multimodal language models Z Wang, S Cai, A Liu, Y Jin, J Hou, B Zhang, H Lin, Z He, Z Zheng, Y Yang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 79 | 2024 |
| Offline Pre-trained Multi-agent Decision Transformer L Meng, M Wen, C Le, X Li, D Xing, W Zhang, Y Wen, H Zhang, J Wang, ... Machine Intelligence Research 20 (2), 233-248, 2023 | 76 | 2023 |
Jun WangProfessor, Computer Science, University College LondonEmail verificata su cs.ucl.ac.uk
