A Single-Loop Deep Actor-Critic Algorithm for Constrained Reinforcement Learning with Provable Convergence

no code implementations • 10 Jun 2023 • Kexuan Wang, An Liu, Baishuo Liu

In spite of the biased policy gradient estimation incurred by the single-loop design and observation reuse, we prove that the SLDAC with a feasible initial point can converge to a Karush-Kuhn-Tuker (KKT) point of the original problem almost surely.

Decision Making reinforcement-learning

Lightweight Facial Attractiveness Prediction Using Dual Label Distribution

no code implementations • 4 Dec 2022 • Shu Liu, Enquan Huang, Yan Xu, Kexuan Wang, Xiaoyan Kui, Tao Lei, Hongying Meng

To make the best use of the dataset, the manual ratings, attractiveness score, and standard deviation are aggregated explicitly to construct a dual label distribution, including the attractiveness distribution and the rating distribution.