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cs.LG2026
Warp RL: Reshaping Base Policy Distributions for Dynamics Adaptation
Ethan Hirschowitz, Fabio Ramos
Residual reinforcement learning adapts a pretrained robot policy by learning an additive correction to its actions. While effective when adaptation amounts to shifting the base pol…
cs.LG2025
Harnessing Bounded-Support Evolution Strategies for Policy Refinement
Ethan Hirschowitz, Fabio Ramos
Improving competent robot policies with on-policy RL is often hampered by noisy, low-signal gradients. We revisit Evolution Strategies (ES) as a policy-gradient proxy and localize…