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News/Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning
arxiv
PublishedApril 30, 2026 at 4:00 AM
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Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning

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arXiv:2508.19900v2 Announce Type: replace Abstract: Offline reinforcement learning (RL) enables learning effective policies from fixed datasets without any environment interaction. Existing methods typically employ policy constraints to mitigate the distribution shift encountered during offline RL t

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#offline-rl#reinforcement-learning#machine-learning#optimization

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