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Sachini Weerasekara

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#machine learning Preprint Sep 2026

REFINEPPO: Learning Continuous Control Policies by Iterative Action Refinement

This work introduces Iterative Action Refinement (IAR), an iterative action-construction method that constructs control actions through a sequence of learned residual corrections, yielding REFINEPPO, which matches or exceeds the performance of standard PPO while demonstrating faster convergence on several tasks.

Sachini Weerasekara, Sagar V. Kamarthi, Jacqueline Isaacs · 1 citation

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