no code implementations • 25 Oct 2023 • Chen Liu, Hongyu Zang, Xin Li, Yong Heng, Yifei Wang, Zhen Fang, Yisen Wang, Mingzhong Wang
Image-based Reinforcement Learning is a practical yet challenging task.
no code implementations • 24 Oct 2023 • Ye Yuan, Xin Li, Yong Heng, Leiji Zhang, Mingzhong Wang
Imitation Learning (IL) aims to discover a policy by minimizing the discrepancy between the agent's behavior and expert demonstrations.
2 code implementations • 31 Dec 2021 • Hongyu Zang, Xin Li, Mingzhong Wang
This work explores how to learn robust and generalizable state representation from image-based observations with deep reinforcement learning methods.
1 code implementation • 1 Jan 2021 • Hongyu Zang, Xin Li, Li Zhang, Peiyao Zhao, Mingzhong Wang
Trust region methods and maximum entropy methods are two state-of-the-art branches used in reinforcement learning (RL) for the benefits of stability and exploration in continuous environments, respectively.
no code implementations • 18 May 2018 • Huiting Hong, Xin Li, Mingzhong Wang
Network embedding has become a hot research topic recently which can provide low-dimensional feature representations for many machine learning applications.