arXivDaily arXiv每日学术速递 周一至周五更新

作者

Sergey Levine

Robotics / Reinforcement Learning

2026-06-29 至 2026-06-29 共收录 1
2605.03065 2026-06-29 cs.LG cs.RO 版本更新

OGPO: Sample Efficient Full-Finetuning of Generative Control Policies

OGPO:生成控制策略的样本高效全微调

Sarvesh Patil, Mitsuhiko Nakamoto, Manan Agarwal, Shashwat Saxena, Jesse Zhang, Giri Anantharaman, Cleah Winston, Chaoyi Pan, Douglas Chen, Nai-Chieh Huang, Zeynep Temel, Oliver Kroemer, Sergey Levine, Abhishek Gupta, Hongkai Dai, Paarth Shah, Max Simchowitz

机构 * University of California, Berkeley(加州大学伯克利分校) UC Berkeley(加州大学伯克利分校)

AI总结 提出OGPO算法,通过离策略评论网络和修改的PPO目标,实现生成控制策略的样本高效微调,在多种操作任务上达到最优性能,并能在无专家数据下微调不良初始化的行为克隆策略。

Comments Website: https://simchowitzlabpublic.github.io/ogpo-site/ Code: https://github.com/simchowitzlabpublic/OGPO_public

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