arxiv
PublishedJuly 14, 2026 at 4:00 AM
▲bullish
Active Offline-to-Online Reinforcement Learning
Publisher summary· verbatim
arXiv:2607.11720v1 Announce Type: cross Abstract: Background: Offline reinforcement learning (RL) enables effective policies to be trained from large, previously collected datasets and subsequently improved through limited online interaction. This offline-to-online RL (O2O-RL) paradigm is particular
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Originally published on arxiv ↗