[27] Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey
Pengyi Li, Jianye Hao, Hongyao Tang, Xian Fu, Yan Zheng, Ke Tang
arXiv preprint 2024 | [Paper]

[26] Designing Biological Sequences without Prior Knowledge using Evolutionary Reinforcement Learning
Xi Zeng, Xiaotian Hao, Hongyao Tang, Zhentai Tang, Shaoqing Jiao, Dazhi Lu, Jiajie Peng
AAAI 2024

[25] Reining Generalization in Offline Reinforcement Learning via Representation Distinction
Yi Ma, Hongyao Tang (Corresponding Author), Dong Li, Zhaopeng Meng
NeurIPS 2023 | [Paper]

[24] Boosting Off-policy RL with Policy Representation and Policy-extended Value Function Approximator
Min Zhang, Jianye Hao, Hongyao Tang, Yan Zheng
ICML 2023 Workshop on Frontiers4LCD | [Paper]

[23] RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution
Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, Xian Fu
ICML 2023 | [Paper]

[22] The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting
Hongyao Tang, Min Zhang, Jianye Hao
arXiv preprint 2023 | [Paper]

[21] 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
ICLR 2023 & DRL Workshop, NeurIPS 2022 | [Paper] [Code]

[20] Exploration in Deep Reinforcement Learning: From Single-Agent to Multi-Agent Domain
Jianye Hao, Tianpei Yang, Hongyao Tang, Chenjia Bai, Jinyi Liu, Zhaopeng Meng, Peng Liu
IEEE Transactions on Neural Networks and Learning Systems (Accepted in 2023 Jan) | [Paper]

[19] Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes
Min Zhang*, Hongyao Tang*, Jianye Hao, Yan Zheng
DRL Workshop, NeurIPS 2022 | [Paper]

[18] 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
ICML 2022 | [Paper] [Code]

[17] 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
IJCAI 2022 | [Paper]

[16] 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
ICLR 2022 & NeurIPS 2021 DRL Workshop Contributed Talk | [Paper]

[15] 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
AAAI 2022 Oral Presentation (< 5%) & NeurIPS 2020 DRL Workshop | [Paper]

[14] An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning
Tianpei Yang*, Weixun Wang*, Hongyao Tang*, Jianye Hao, Zhaopeng Meng, Hangyu Mao, Dong Li, Wulong Liu, Yingfeng Chen, Yujing Hu, Changjie Fan, Chengwei Zhang
NeurIPS 2021 | [Paper]

[13] 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
AAAI 2021 | [Paper]

[12] 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
AAAI 2021 & NeurIPS 2020 DRL Workshop | [Paper]

[11] Addressing Action Oscillations through Learning Policy Inertia
Chen Chen*, Hongyao Tang*, Jianye Hao, Wulong Liu, Zhaopeng Meng
AAAI 2021 | [Paper]

[10] Uncertainty-Aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning
Tong Sang, Hongyao Tang, Jianye Hao, Yan Zheng, Zhaopeng Meng
DAI 2021 | [Paper]

[9] ED2: An Environment Dynamics Decomposition Framework for World Model Construction
Cong Wang, Tianpei Yang, Jianye Hao, Yan Zheng, Hongyao Tang, Fazl Barez, Jinyi Liu, Jiajie Peng, Haiyin Piao, Zhixiao Sun
arXiv preprint (2021) | [Paper]

[8] 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
ICML 2020 | [Paper]

[7] Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Ben Liao, Kun Shao, Guangyong Chen, Wulong Liu, Hongyao Tang
arXiv preprint (2020) | [Paper]

[6] KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge
Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma, Yihai Duan, Yan Zheng
IJCAI 2020 | [Paper]

[5] MGHRL: Meta Goal-Generation for Hierarchical Reinforcement Learning
Haotian Fu, Hongyao Tang, Jianye Hao, Wulong Liu, Chen Chen
DAI 2020 | [Paper]

[4] Mastering Basketball With Deep Reinforcement Learning: An Integrated Curriculum Training Approach
Hangtian Jia, Chunxu Ren, Yujing Hu, Yingfeng Chen, Tangjie Lv, Changjie Fan, Hongyao Tang, Jianye Hao
AAMAS 2020 Extended Abstract | [Paper]

[3] Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction
Hongyao Tang, Jianye Hao, Tangjie Lv, Yingfeng Chen, Zongzhang Zhang, Hangtian Jia, Chunxu Ren, Yan Zheng, Changjie Fan, Li Wang
arXiv preprint (2019) | [Paper]

[2] Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces
Haotian Fu, Hongyao Tang, Jianye Hao, Zihan Lei, Yingfeng Chen, Changjie Fan
IJCAI 2019 | [Paper]

[1] An Optimal Rewiring Strategy for Cooperative Multiagent Social Learning
Hongyao Tang, Jianye Hao, Li Wang, Tim Baarslag, Zan Wang
AAAI 2019 Student Abstract Finalist & AAMAS 2019 Extended Abstract | [Paper]