Tang, Hongyao

39 publications

NeurIPS 2025 COLA: Towards Efficient Multi-Objective Reinforcement Learning with Conflict Objective Regularization in Latent Space Pengyi Li, Hongyao Tang, Yifu Yuan, Jianye Hao, Zibin Dong, Yan Zheng

NeurIPS 2025 CORE: Collaborative Optimization with Reinforcement Learning and Evolutionary Algorithm for Floorplanning Pengyi Li, Shixiong Kai, Jianye Hao, Ruizhe Zhong, Hongyao Tang, Zhentao Tang, Mingxuan Yuan, Junchi Yan

ICLRW 2025 Can We Optimize Deep RL Policy Weights as Trajectory Modeling? Hongyao Tang

NeurIPS 2025 FANS: A Flatness-Aware Network Structure for Generalization in Offline Reinforcement Learning Da Wang, Yi Ma, Ting Guo, Hongyao Tang, Wei Wei, Jiye Liang

NeurIPS 2025 LaRes: Evolutionary Reinforcement Learning with LLM-Based Adaptive Reward Search Pengyi Li, Hongyao Tang, Jinbin Qiao, Yan Zheng, Jianye Hao

ICML 2025 Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro, Aaron Courville, Glen Berseth

ICML 2025 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

AAAI 2024 Designing Biological Sequences Without Prior Knowledge Using Evolutionary Reinforcement Learning Xi Zeng, Xiaotian Hao, Hongyao Tang, Zhentao Tang, Shaoqing Jiao, Dazhi Lu, Jiajie Peng

NeurIPSW 2024 Efficient Design-and-Control Automation with Reinforcement Learning and Adaptive Exploration Jiajun Fan, Hongyao Tang, Michael Przystupa, Mariano Phielipp, Santiago Miret, Glen Berseth

ICML 2024 EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search Pengyi Li, Yan Zheng, Hongyao Tang, Xian Fu, Jianye Hao

NeurIPSW 2024 HuLE-Nav: Human-like Exploration for Zero-Shot Object Navigation via Vision-Language Models Peilong Han, Min Zhang, Jianye Hao, Hongyao Tang, Yan Zheng

NeurIPS 2024 Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn Hongyao Tang, Glen Berseth

NeurIPSW 2024 Self-Supervised Bisimulation Action Chunk Representation for Efficient RL Lei Shi, Jianye Hao, Hongyao Tang, Zibin Dong, Yan Zheng

NeurIPSW 2024 Self-Supervised Bisimulation Action Chunk Representation for Efficient RL Lei Shi, Jianye Hao, Hongyao Tang, Zibin Dong, Yan Zheng

NeurIPS 2024 The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in a Low-Dimensional Space Hongyao Tang, Min Zhang, Chen Chen, Jianye Hao

ICML 2024 Value-Evolutionary-Based Reinforcement Learning Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, Fazl Barez

ICMLW 2024 What Can VLMs Do for Zero-Shot Embodied Task Planning? Xian Fu, Min Zhang, Jianye Hao, Peilong Han, Hao Zhang, Lei Shi, Hongyao Tang

ICMLW 2024 What Can VLMs Do for Zero-Shot Embodied Task Planning? Xian Fu, Min Zhang, Jianye Hao, Peilong Han, Hao Zhang, Lei Shi, Hongyao Tang

ICMLW 2023 Boosting Off-Policy RL with Policy Representation and Policy-Extended Value Function Approximator Min Zhang, Jianye Hao, Hongyao Tang, Yan Zheng

ICLR 2023 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

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

NeurIPS 2023 Reining Generalization in Offline Reinforcement Learning via Representation Distinction Yi Ma, Hongyao Tang, Dong Li, Zhaopeng Meng

NeurIPSW 2022 ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation Pengyi Li, Hongyao Tang, Jianye Hao, Yan Zheng, Xian Fu, Zhaopeng Meng

ICLR 2022 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

ICLRW 2022 PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations Sang Tong, Hongyao Tang, Yi Ma, Jianye Hao, Yan Zheng, Zhaopeng Meng, Boyan Li, Zhen Wang

IJCAI 2022 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

ICML 2022 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

NeurIPSW 2022 Towards a Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes Min Zhang, Hongyao Tang, Jianye Hao, Yan Zheng

NeurIPSW 2022 A Unified Framework to Understand Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective Xinwei Zhang, Nicola Elia, Mingyi Hong

AAAI 2022 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 2021 Addressing Action Oscillations Through Learning Policy Inertia Chen Chen, Hongyao Tang, Jianye Hao, Wulong Liu, Zhaopeng Meng

NeurIPS 2021 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

AAAI 2021 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

NeurIPSW 2021 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

AAAI 2021 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

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

ICML 2020 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

AAAI 2019 An Optimal Rewiring Strategy for Cooperative Multiagent Social Learning Hongyao Tang, Jianye Hao, Li Wang, Tim Baarslag, Zan Wang

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