| Multi-agent deep reinforcement learning with type-based hierarchical group communication H Jiang, D Shi, C Xue, Y Wang, G Wang, Y Zhang Applied Intelligence 51, 5793-5808, 2021 | 18 | 2021 |
| Multi actor hierarchical attention critic with RNN-based feature extraction D Shi, C Zhao, Y Wang, H Yang, G Wang, H Jiang, C Xue, S Yang, ... Neurocomputing 471, 79-93, 2022 | 12 | 2022 |
| AHAC: actor hierarchical attention critic for multi-agent reinforcement learning Y Wang, D Shi, C Xue, H Jiang, G Wang, P Gong 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | 12 | 2020 |
| Efficient state representation with artificial potential fields for reinforcement learning H Jiang, S Li, J Zhang, Y Zhu, X Xu, D Liu Complex & Intelligent Systems 9 (5), 4911-4922, 2023 | 7 | 2023 |
| Ghgc: Goal-based hierarchical group communication in multi-agent reinforcement learning H Jiang, D Shi, C Xue, Y Wang, G Wang, Y Zhang 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | 5 | 2020 |
| Bic-ddpg: Bidirectionally-coordinated nets for deep multi-agent reinforcement learning G Wang, D Shi, C Xue, H Jiang, Y Wang International Conference on Collaborative Computing: Networking …, 2020 | 4 | 2020 |
| Diverse effective relationship exploration for cooperative multi-agent reinforcement learning H Jiang, Y Liu, S Li, J Zhang, X Xu, D Liu Proceedings of the 31st ACM International Conference on Information …, 2022 | 2 | 2022 |
| Friend-or-foe deep deterministic policy gradient H Jiang, D Shi, C Xue, Y Wang, G Wang, Y Zhang 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | 2 | 2020 |
| Generative subgoal oriented multi-agent reinforcement learning through potential field S Li, H Jiang, Y Liu, J Zhang, X Xu, D Liu Neural Networks 179, 106552, 2024 | | 2024 |
