Interactive coupling between a tree and raindrops. - Meng Yang 011; Longsheng Jiang; Xiaosheng Li; Youquan Liu; Xuehui Liu; Enhua Wu (Comput. Animat. Virtual Worlds, 2012)

A regret-based autonomy allocation scheme for human-robot shared vision systems in collaborative assembly in manufacturing. - S. M. Mizanoor Rahman; Zhanrui Liao; Longsheng Jiang; Yue Wang 011 (CASE, 2016)

A quantitative measure of regret in decision-making for human-robot collaborative search tasks. - Zhanrui Liao; Longsheng Jiang; Yue Wang 011 (ACC, 2017)

A Human-Computer Interface Design for Quantitative Measure of Regret Theory. - Longsheng Jiang; Yue Wang 011 (CoRR, 2018)

Respect Your Emotion: Human-Multi-Robot Teaming based on Regret Decision Model. - Longsheng Jiang; Yue Wang 011 (CASE, 2019)

Autonomous Driving using Safe Reinforcement Learning by Incorporating a Regret-based Human Lane-Changing Decision Model. - Dong Chen 016; Longsheng Jiang; Yue Wang 011; Zhaojian Li (ACC, 2020)

Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic. - Dong Chen 016; Zhaojian Li; Yongqiang Wang 001; Longsheng Jiang; Yue Wang 011 (CoRR, 2021)

A Bayesian Trust Inference Model for Human-Multi-Robot Teams. - Maziar Fooladi Mahani; Longsheng Jiang; Yue Wang 011 (Int. J. Soc. Robotics, 2021)

Risk-aware Decision-making in Human-multi-robot Collaborative Search: A Regret Theory Approach. - Longsheng Jiang; Yue Wang 011 (J. Intell. Robotic Syst., 2022)

A Personalized Computational Model for Human-Like Automated Decision-Making. - Longsheng Jiang; Yue Wang 011 (IEEE Trans Autom. Sci. Eng., 2022)

Risk Representation, Perception, and Propensity in an Integrated Human Lane-Change Decision Model. - Longsheng Jiang; Dong Chen 016; Zhaojian Li; Yue Wang 011 (IEEE Trans. Intell. Transp. Syst., 2022)

Deep Multi-Agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic. - Dong Chen 016; Mohammad R. Hajidavalloo; Zhaojian Li; Kaian Chen; Yongqiang Wang 001; Longsheng Jiang; Yue Wang 011 (IEEE Trans. Intell. Transp. Syst., 2023)