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Updated: Jan 16, 2026

Movement Retraining using Real-time Feedback of Performance
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Published on: January 17, 2013

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离线到在线的强化学习,具有高效的不受约束的微调

Jun Zheng1, Runda Jia2, Shaoning Liu1

  • 1College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China.

Neural networks : the official journal of the International Neural Network Society
|September 25, 2025
PubMed
概括

本研究引入了一个高效的不受约束的微调框架,用于线下到线上强化学习. 该方法通过使离线数据集之外的彻底探索成为可能,从而提高政策绩效,从而实现更好的样本效率.

关键词:
隐藏空间模型 隐藏空间模型层规范化的层规范化.离线到在线的强化学习.代表性的学习学习.

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