LASER: Latent Space Adjoint Matching for Support-Constrained Entropy-Regularized Offline RL
arXiv:2610.08989v1 Announce Type: new Abstract: While offline reinforcement learning (RL) enables policy optimization from static datasets without costly online interaction, it remains bottlenecked by the risk of executing out-of-distribution (OOD) actions. Recent approaches mitigate this by learni…
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- 2026-10-08 04:00 · arXiv cs.LG
LASER: Latent Space Adjoint Matching for Support-Constrained Entropy-Regularized Offline RL