Operator-Guided Invariance Learning for Continuous Reinforcement Learning
arXiv:2605.06500v1 Announce Type: cross
Abstract: Reinforcement learning (RL) with continuous time and state/action spaces is often data-intensive and brittle under nuisance variability and shift, motivating methods that exploit value-preserving struc…