arXiv Machine Learning June 16, 2026 By Yi Zhao, Aidan Scannell, Wenshuai Zhao, Yuxin Hou, Tianyu Cui, Le Chen, Dieter B\"uchler, Arno Solin, Juho Kannala, Joni Pajarinen

Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data

Read the original on arXiv Machine Learning →

arXiv:2502. 19544v3 Announce Type: replace Abstract: Leveraging offline data is a promising way to improve the sample efficiency of online reinforcement learning (RL).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

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arXiv AI

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