| Learning to utilize shaping rewards: A new approach of reward shaping Y Hu, W Wang, H Jia, Y Wang, Y Chen, J Hao, F Wu, C Fan Advances in Neural Information Processing Systems 33, 15931-15941, 2020 | 136 | 2020 |
| Hierarchical deep multiagent reinforcement learning with temporal abstraction H Tang, J Hao, T Lv, Y Chen, Z Zhang, H Jia, C Ren, Y Zheng, Z Meng, ... arXiv preprint arXiv:1809.09332, 2018 | 73 | 2018 |
| Towards unifying behavioral and response diversity for open-ended learning in zero-sum games X Liu, H Jia, Y Wen, Y Hu, Y Chen, C Fan, Z Hu, Y Yang Advances in Neural Information Processing Systems 34, 941-952, 2021 | 41 | 2021 |
| Fever basketball: A complex, flexible, and asynchronized sports game environment for multi-agent reinforcement learning H Jia, Y Hu, Y Chen, C Ren, T Lv, C Fan, C Zhang arXiv preprint arXiv:2012.03204, 2020 | 28 | 2020 |
| 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 arXiv preprint arXiv:2106.04958, 2021 | 17 | 2021 |
| Mastering basketball with deep reinforcement learning: An integrated curriculum training approach H Jia, C Ren, Y Hu, Y Chen, T Lv, C Fan, H Tang, J Hao Proceedings of the 19th International Conference on Autonomous Agents and …, 2020 | 10 | 2020 |
