@article{han2024what,author={Han, Songyang and Su, Sanbao and He, Sihong and Han, Shuo and Yang, Haizhao and Zou, Shaofeng and Miao, Fei},title={What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?},journal={Transactions on Machine Learning Research (TMLR)},year={2024},}
@inproceedings{he2023robust_iros_uncertain_model,title={A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems},author={He, Sihong and Wang, Yue and Han, Shuo and Zou, Shaofeng and Miao, Fei},booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},pages={5637--5644},year={2023},organization={IEEE},}
@inproceedings{he2023robust_iros_uncertain_state,title={Robust electric vehicle balancing of autonomous mobility-on-demand system: A multi-agent reinforcement learning approach},author={He, Sihong and Han, Shuo and Miao, Fei},booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},pages={5471--5478},year={2023},organization={IEEE},}
@article{he2023robust_tmlr,title={Robust Multi-Agent Reinforcement Learning with State Uncertainty},author={He, Sihong and Han, Songyang and Su, Sanbao and Han, Shuo and Zou, Shaofeng and Miao, Fei},journal={Transactions on Machine Learning Research (TMLR)},issn={2835-8856},year={2023},url={https://openreview.net/forum?id=CqTkapZ6H9}}
@article{he2023data_tits,author={He, Sihong and Zhang, Zhili and Han, Shuo and Pepin, Lynn and Wang, Guang and Zhang, Desheng and Stankovic, John A. and Miao, Fei},journal={IEEE Transactions on Intelligent Transportation Systems},title={Data-Driven Distributionally Robust Electric Vehicle Balancing for Autonomous Mobility-on-Demand Systems Under Demand and Supply Uncertainties},year={2023},pages={1-17},doi={10.1109/TITS.2023.3237804}}
@article{he2023robust_rmarl_ai4abm,title={Robust Multi-Agent Reinforcement Learning Considering State Uncertainties},author={He, Sihong and Han, Songyang and Su, Sanbao and Han, Shuo and Zou, Shaofeng and Miao, Fei},journal={AI4ABM Workshop at the International Conference on Learning Representations (ICLR)},year={2023}}
@article{he2023robust_ev_ai4abm,title={A Robust and Constrained Multi-Agent Reinforcement Learning Method for Electric Vehicle Rebalancing in AMoD Systems},author={He, Sihong and Wang, Yue and Han, Shuo and Zou, Shaofeng and Miao, Fei},journal={AI4ABM Workshop at the International Conference on Learning Representations (ICLR)},year={2023}}
@article{su2022uncertainty,title={Uncertainty quantification of collaborative detection for self-driving},author={Su, Sanbao and Li, Yiming and He, Sihong and Han, Songyang and Feng, Chen and Ding, Caiwen and Miao, Fei},journal={IEEE International Conference on Robotics and Automation (ICRA)},year={2023}}
@inproceedings{han2022what,title={What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?},author={Han, Songyang and Su, Sanbao and He, Sihong and Han, Shuo and Yang, Haizhao and Miao, Fei},booktitle={ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems},year={2022},}
@article{miao2021data_tcps,title={Data-driven distributionally robust optimization for vehicle balancing of mobility-on-demand systems},author={Miao, Fei and He, Sihong and Pepin, Lynn and Han, Shuo and Hendawi, Abdeltawab and Khalefa, Mohamed E and Stankovic, John A and Pappas, George},journal={ACM Transactions on Cyber-Physical Systems},url={https://dl.acm.org/doi/10.1145/3418287},volume={5},number={2},pages={1--27},year={2021},publisher={ACM New York, NY, USA}}
@inproceedings{he2020data_iros,author={He, Sihong and Pepin, Lynn and Wang, Guang and Zhang, Desheng and Miao, Fei},booktitle={2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},pages={2165--2172},year={2020},organization={IEEE}}