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cs.LG2026
Rethinking the Suitability of Reinforcement Learning Algorithms Under Practical Transfer Constraints
Hany Hamed, Abhishek Naik, Colin Bellinger +1
Transfer-oriented reinforcement learning requires evaluating algorithms along dimensions that go beyond standard sample efficiency. We focus on two dimensions: practical efficiency…
cs.RO2026
Benchmarking Action Spaces in Reinforcement Learning for Vision-based Robotic Manipulation
Seyed Alireza Azimi, Homayoon Farrahi, Abhishek Naik +2
In real-world reinforcement learning (RL), the choice of action space can play a key role in shaping motion smoothness, safety, and overall task performance. In this study, we eval…