1 code implementation • 16 Feb 2022 • Haojie Shi, Max Q. -H. Meng
Furthermore, most Koopman-based algorithms only consider nonlinear systems with linear control input, resulting in lousy prediction and control performance when the system is fully nonlinear with the control input.
1 code implementation • 14 Sep 2021 • Haojie Shi, Bo Zhou, Hongsheng Zeng, Fan Wang, Yueqiang Dong, Jiangyong Li, Kang Wang, Hao Tian, Max Q. -H. Meng
However, due to the complex nonlinear dynamics in quadrupedal robots and reward sparsity, it is still difficult for RL to learn effective gaits from scratch, especially in challenging tasks such as walking over the balance beam.
no code implementations • CUHK Course IERG5350 2020 • Haojie Shi, LI ANG
Reinforcement Learning, a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex and uncertain environment.
no code implementations • 30 Sep 2019 • Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kummerle, Hendrik Konigshof, Christoph Stiller, Arnaud de La Fortelle, Masayoshi Tomizuka
3) The driving behavior is highly interactive and complex with adversarial and cooperative motions of various traffic participants.