Skip to content
Sagan

Paper

UNIQ: Conformal Calibration for Adaptive Conservatism in Offline Reinforcement Learning

Unreadunread

AI summary

arXiv:2606. 07592v1 Announce Type: new Abstract: Offline reinforcement learning requires careful conservatism to mitigate distribution shift, yet most existing methods apply a fixed penalty uniformly across all states regardless of local data coverage.