no code implementations • 24 Feb 2024 • Shuyu Yin, Qixuan Zhou, Fei Wen, Tao Luo
However, existing performance analyses ignores the unique characteristics of continuous-time control problems, is unable to directly estimate the generalization error of the Bellman optimal loss and require a boundedness assumption.
no code implementations • 25 May 2022 • Shuyu Yin, Tao Luo, Peilin Liu, Zhi-Qin John Xu
In this work, we perform extensive experiments to show that TD outperforms RG, that is, when the training leads to a small Bellman residual error, the solution found by TD has a better policy and is more robust against the perturbation of neural network parameters.
no code implementations • 3 Dec 2018 • Yanjun Li, Hengtong Kang, Ketian Ye, Shuyu Yin, Xiaolin Li
In this paper, we propose a novel protein folding framework FoldingZero, self-folding a de novo protein 2D HP structure from scratch based on deep reinforcement learning.