| Multi-agent game abstraction via graph attention neural network Y Liu, W Wang, Y Hu, J Hao, X Chen, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7211-7218, 2020 | 17 | 2020 |
| From few to more: Large-scale dynamic multiagent curriculum learning W Wang, T Yang, Y Liu, J Hao, X Hao, Y Hu, Y Chen, C Fan, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7293-7300, 2020 | 11 | 2020 |
| Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns. Y Liu, Y Hu, Y Gao, Y Chen, C Fan IJCAI, 457-463, 2019 | 5 | 2019 |
| Reinforcement learning from algorithm model to industry innovation: A foundation stone of future artificial intelligence D Shaokang, C Jiarui, LIU Yong, BAO Tianyi, GAO Yang ZTE Communications 17 (3), 31-41, 2019 | 1 | 2019 |
| Automatic data augmentation by learning the deterministic policy Y Shi, T Qin, Y Liu, J Lu, Y Gao, D Shen arXiv preprint arXiv:1910.08343, 2019 | 1 | 2019 |
| Action Semantics Network: Considering the Effects of Actions in Multiagent Systems W Wang, T Yang, Y Liu, J Hao, X Hao, Y Hu, Y Chen, C Fan, Y Gao arXiv preprint arXiv:1907.11461, 2019 | | 2019 |
