4 papers
GCHR : Goal-Conditioned Hindsight Regularization for Sample-Efficient Reinforcement Learning
Xing Lei, Wenyan Yang, Kaiqiang Ke +4
Goal-conditioned reinforcement learning (GCRL) with sparse rewards remains a fundamental challenge in reinforcement learning. While hindsight experience replay (HER) has shown prom…
Closing the Gap between TD Learning and Supervised Learning with -Conditioned Maximization
Xing Lei, Zifeng Zhuang, Shentao Yang +6
Recently, supervised learning (SL) methodology has emerged as an effective approach for offline reinforcement learning (RL) due to their simplicity, stability, and efficiency. Howe…
MGDA: Model-based Goal Data Augmentation for Offline Goal-conditioned Weighted Supervised Learning
Xing Lei, Xuetao Zhang, Donglin Wang
Recently, a state-of-the-art family of algorithms, known as Goal-Conditioned Weighted Supervised Learning (GCWSL) methods, has been introduced to tackle challenges in offline goal-…
Q-WSL: Optimizing Goal-Conditioned RL with Weighted Supervised Learning via Dynamic Programming
Xing Lei, Xuetao Zhang, Zifeng Zhuang +1
A novel class of advanced algorithms, termed Goal-Conditioned Weighted Supervised Learning (GCWSL), has recently emerged to tackle the challenges posed by sparse rewards in goal-co…