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About this paper
Sanghyun Hahn, Jonghyun Choi
ACPPO-Corr pairs chunk-level plans with stepwise state feedback in online PPO for simulated continuous robotics. It adds corrections to planned actions within each chunk, while a regularizer limits their size. Across 25 tasks, it improves final normalized IQM by 30.4% over PPO, but this result is limited to state-based simulation and does not imply faster training or universal gains.
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