| A survey of deep reinforcement learning in video games K Shao, Z Tang, Y Zhu, N Li, D Zhao arXiv preprint arXiv:1912.10944, 2019 | 200 | 2019 |
| Starcraft micromanagement with reinforcement learning and curriculum transfer learning K Shao, Y Zhu, D Zhao IEEE Transactions on Emerging Topics in Computational Intelligence 3 (1), 73-84, 2018 | 196 | 2018 |
| Qatten: A general framework for cooperative multiagent reinforcement learning Y Yang, J Hao, B Liao, K Shao, G Chen, W Liu, H Tang arXiv preprint arXiv:2002.03939, 2020 | 190 | 2020 |
| Smarts: An open-source scalable multi-agent rl training school for autonomous driving M Zhou, J Luo, J Villella, Y Yang, D Rusu, J Miao, W Zhang, M Alban, ... Conference on Robot Learning, 264-285, 2021 | 175 | 2021 |
| Deep reinforcement learning with experience replay based on SARSA D Zhao, H Wang, K Shao, Y Zhu 2016 IEEE symposium series on computational intelligence (SSCI), 1-6, 2016 | 151 | 2016 |
| Multi-agent determinantal q-learning Y Yang, Y Wen, J Wang, L Chen, K Shao, D Mguni, W Zhang International Conference on Machine Learning, 10757-10766, 2020 | 74 | 2020 |
| Review of deep reinforcement learning and discussions on the development of computer Go D Zhao, K Shao, Y Zhu, D Li, Y Chen, H Wang, DR Liu, T Zhou, CH Wang Control Theory & Applications 33 (6), 701-717, 2016 | 69 | 2016 |
| Recent progress of deep reinforcement learning: from AlphaGo to AlphaGo Zero Z Tang, K Shao, D Zhao, Y Zhu Control Theory & Applications 34 (12), 1529-1546, 2017 | 47 | 2017 |
| Learning battles in vizdoom via deep reinforcement learning K Shao, D Zhao, N Li, Y Zhu 2018 IEEE Conference on Computational Intelligence and Games (CIG), 1-4, 2018 | 37 | 2018 |
| Cooperative reinforcement learning for multiple units combat in StarCraft K Shao, Y Zhu, D Zhao 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-6, 2017 | 22 | 2017 |
| Move prediction in Gomoku using deep learning K Shao, D Zhao, Z Tang, Y Zhu 2016 31st Youth Academic Annual Conference of Chinese Association of …, 2016 | 22 | 2016 |
| A review of computational intelligence for StarCraft AI Z Tang, K Shao, Y Zhu, D Li, D Zhao, T Huang 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 1167-1173, 2018 | 21 | 2018 |
| Cooperative multi-agent transfer learning with level-adaptive credit assignment T Zhou, F Zhang, K Shao, K Li, W Huang, J Luo, W Wang, Y Yang, H Mao, ... arXiv preprint arXiv:2106.00517, 2021 | 19 | 2021 |
| ADP with MCTS algorithm for Gomoku Z Tang, D Zhao, K Shao, LV Le 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2016 | 17 | 2016 |
| Traj-mae: Masked autoencoders for trajectory prediction H Chen, J Wang, K Shao, F Liu, J Hao, C Guan, G Chen, PA Heng Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 15 | 2023 |
| Chessgpt: Bridging policy learning and language modeling X Feng, Y Luo, Z Wang, H Tang, M Yang, K Shao, D Mguni, Y Du, J Wang Advances in Neural Information Processing Systems 36, 2024 | 11 | 2024 |
| Visual navigation with actor-critic deep reinforcement learning K Shao, D Zhao, Y Zhu, Q Zhang 2018 International Joint Conference on Neural Networks (IJCNN), 1-6, 2018 | 11 | 2018 |
| Pangu-agent: A fine-tunable generalist agent with structured reasoning F Christianos, G Papoudakis, M Zimmer, T Coste, Z Wu, J Chen, ... arXiv preprint arXiv:2312.14878, 2023 | 7 | 2023 |
| Multiagent q-learning with sub-team coordination W Huang, K Li, K Shao, T Zhou, M Taylor, J Luo, D Wang, H Mao, J Hao, ... Advances in Neural Information Processing Systems 35, 29427-29439, 2022 | 7 | 2022 |
| Heterogeneous graph neural network-based imitation learning for gate sizing acceleration X Zhou, J Ye, CW Pui, K Shao, G Zhang, B Wang, J Hao, G Chen, ... Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided …, 2022 | 7 | 2022 |
Dongbin ZhaoInstitute of Automation, Chinese Academy of Sciencesia.ac.cn의 이메일 확인됨
