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Zhaoxing Yang (æšć æ) I'm a third-year Ph.D. candidate in John Hopcroft Center, Shanghai Jiao Tong University, fortunate to be advised by Prof. Haiming Jin. Before that, I obtained my master degree in Computer Science and Engineering from Shanghai Jiao Tong University in 2022, and bachelor degree in Information Security from Huazhong University of Science and Technology in 2019. My research interest lies in addressing various challenges in applying reinforcement learning algorithms to practical sequential decision-making applications. These challenges include, but are not limited to, satisfying constraint conditions, enhancing robustness, and facilitating multi-agent interaction. Recently, I have developed a profound interest in interpretable policies, particularly the programmatic policy class. |
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Publications (* denotes equal contribution) |
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Rethinking Order Dispatching in Online Ride-Hailing Platforms
Zhaoxing Yang, Haiming Jin, Guiyun Fan, Min Lu, Yiran Liu, Xinlang Yue, Hao Pan, Zhe Xu, Guobin Wu, Qun Li, Xiaotong Wang, Jiecheng Guo KDD, 2024 paper / code / technique report |
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Risk-Aware Constrained Reinforcement Learning with Non-Stationary Policies
Zhaoxing Yang, Haiming Jin, Tang Yao, Guiyun Fan AAMAS, 2024 paper / code / appendix |
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Optimizing Long-Term Efficiency and Fairness in Ride-Hailing under Budget Constraint via Joint Order Dispatching and Driver Repositioning
Jiahui Sun, Haiming Jin, Zhaoxing Yang, Lu Su IEEE Transactions on Knowledge and Data Engineering (TKDE) paper |
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Multi-Intersection Management for Connected Autonomous Vehicles by Reinforcement Learning
Haiming Jin, Yifei Wei, Zhaoxing Yang, Zirui Liu, Guiyun Fan ICDCS, 2023 paper |
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DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning
Zhaoxing Yang, Haiming Jin, Rong Ding, Haoyi You, Guiyun Fan, Xinbing Wang, Chenghu Zhou AAAI, 2023 paper / code |
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User-Oriented Robust Reinforcement Learning
Haoyi You, Beichen Yu, Haiming Jin, Zhaoxing Yang, Jiahui Sun AAAI, 2023 paper |
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Optimizing Long-Term Efficiency and Fairness in Ride-Hailing via Joint Order Dispatching and Driver Repositioning
Jiahui Sun, Haiming Jin, Zhaoxing Yang, Lu Su, Xinbing Wang KDD, 2022 paper |
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Constrained Multi-Agent Reinforcement Learning for Managing Electric Self-Driving Taxis
Zhaoxing Yang, Guiyun Fan, Haiming Jin ICPADS, 2021 paper / code |
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Multi-Agent Reinforcement Learning for Urban Crowd Sensing with For-Hire Vehicles
Rong Ding*, Zhaoxing Yang*, Yifei Wei, Haiming Jin, Xinbing Wang INFOCOM, 2021 paper |
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Joint Charging and Relocation Recommendation for E-Taxi Drivers via Multi-Agent Mean Field Hierarchical Reinforcement Learning
Enshu Wang, Rong Ding, Zhaoxing Yang, Haiming Jin, Chenglin Miao, Lu Su, Fan Zhang, Chunming Qiao, Xinbing Wang IEEE Transactions on Mobile Computing (TMC) paper |
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Enabling optimal control under demand elasticity for electric vehicle charging systems
Guiyun Fan, Zhaoxing Yang, Haiming Jin, Xiaoying Gan, Xinbing Wang IEEE Transactions on Mobile Computing (TMC) paper |
Talks |
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"Risk-Aware Constrained Reinforcement Learning with Non-Stationary Policies" Presentation at AAMAS, Auckland, New Zealand |
2024.5 |
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"Multi-Intersection Management for Connected Autonomous Vehicles by Reinforcement Learning" Presentation at ICDCS, Hong Kong, China |
2023.7 |
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"Recent Advances on Offline Reinforcement Learning" Talk at Didi Chuxing, Beijing, China |
2022.12 |
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"DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning" Presentation at AAAI, Online |
2022.12 |
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"Constrained Multi-Agent Reinforcement Learning for Managing Electric Self-Driving Taxis" Presentation at ICPADS, Online |
2021.11 |
Internships |
| Intern at Didi Chuxing as a researcher of GAIA project, Beijing, China. |
2022.10-2023.9 |
Services |
| Reviewer for |
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Teaching Assistantships |
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Useful Links |