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cs.LG2026
Delayed homomorphic reinforcement learning for environments with delayed feedback
Jongsoo Lee, Jangwon Kim, Soohee Han
Reinforcement learning in real-world systems often involves delayed feedback, which breaks the Markov assumption and impedes both learning and control. Canonical augmentation-based…
cs.LG2026
Reinforcement Learning via Conservative Agent for Environments with Random Delays
Jongsoo Lee, Jangwon Kim, Jiseok Jeong +1
Real-world reinforcement learning applications are often hindered by delayed feedback from environments, which violates the Markov assumption and introduces significant challenges.…