| 2025 | ICML | R*: Efficient Reward Design via Reward Structure Evolution and Parameter Alignment Optimization with Large Language Models. | Pengyi Li, Jianye Hao, Hongyao Tang, Yifu Yuan, Jinbin Qiao, Zibin Dong, Yan Zheng |
| 2025 | ICML | Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. | Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth |
| 2024 | AAAI | Designing Biological Sequences without Prior Knowledge Using Evolutionary Reinforcement Learning. | Xi Zeng, Xiaotian Hao, Hongyao Tang, Zhentao Tang, Shaoqing Jiao, Dazhi Lu, Jiajie Peng |
| 2024 | ICML | EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search. | Pengyi Li, Yan Zheng, Hongyao Tang, Xian Fu, Jianye Hao |
| 2024 | ICML | Value-Evolutionary-Based Reinforcement Learning. | Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, Fazl Barez |
| 2023 | ICLR | ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation. | Jianye Hao, Pengyi Li, Hongyao Tang, Yan Zheng, Xian Fu, Zhaopeng Meng |
| 2023 | ICML | RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution. | Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, Xian Fu |
| 2022 | AAAI | What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator. | Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang |
| 2022 | ICLR | HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation. | Boyan Li, Hongyao Tang, Yan Zheng, Jianye Hao, Pengyi Li, Zhen Wang, Zhaopeng Meng, Li Wang |
| 2022 | ICML | PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration. | Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Wenyuan Tao, Zhen Wang |
| 2022 | IJCAI | PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations. | Tong Sang, Hongyao Tang, Yi Ma, Jianye Hao, Yan Zheng, Zhaopeng Meng, Boyan Li, Zhen Wang |
| 2021 | AAAI | Addressing Action Oscillations through Learning Policy Inertia. | Chen Chen, Hongyao Tang, Jianye Hao, Wulong Liu, Zhaopeng Meng |
| 2021 | AAAI | Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning. | Haotian Fu, Hongyao Tang, Jianye Hao, Chen Chen, Xidong Feng, Dong Li, Wulong Liu |
| 2021 | AAAI | Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction. | Hongyao Tang, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Jianye Hao |
| 2020 | ICANN | Improving Multi-agent Reinforcement Learning with Imperfect Human Knowledge. | Xiaoxu Han, Hongyao Tang, Yuan Li, Guang Kou, Leilei Liu |
| 2020 | ICML | Q-value Path Decomposition for Deep Multiagent Reinforcement Learning. | Yaodong Yang, Jianye Hao, Guangyong Chen, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei |
| 2020 | IJCAI | KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge. | Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma, Yihai Duan, Yan Zheng |
| 2019 | AAAI | An Optimal Rewiring Strategy for Cooperative Multiagent Social Learning. | Hongyao Tang, Jianye Hao, Li Wang, Tim Baarslag, Zan Wang |
| 2019 | IJCAI | Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces. | Haotian Fu, Hongyao Tang, Jianye Hao, Zihan Lei, Yingfeng Chen, Changjie Fan |