Delayed homomorphic reinforcement learning for environments with delayed feedback

arXiv:2604.03641v2 Announce Type: replace-cross Abstract: Reinforcement learning in real-world systems often involves delayed feedback, which breaks the Markov assumption and impedes both learning and control. Canonical augmentation-based approaches cause state-space explosion, which imposes a...