3 papers
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…
cs.CV2025
Dynamic Object Masks as Goal Representations for Visual Goal-Conditioned Reinforcement Learning
Fahim Shahriar, Cheryl Wang, Alireza Azimi +6
Goal-conditioned reinforcement learning (GCRL) offers a unified way to pursue diverse tasks, yet most existing methods rely on state- or position-based goal representations that ar…