3 papers
cs.LG2026
Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
Yilei Chen, Vittorio Giammarino, James Queeney +1
Adversarial Imitation Learning (AIL) faces challenges with sample inefficiency because of its reliance on sufficient on-policy data to evaluate the performance of the current polic…
cs.LG2025
GRAM: Generalization in Deep RL with a Robust Adaptation Module
James Queeney, Xiaoyi Cai, Alexander Schperberg +3
The reliable deployment of deep reinforcement learning in real-world settings requires the ability to generalize across a variety of conditions, including both in-distribution scen…
cs.RO2024
PIETRA: Physics-Informed Evidential Learning for Traversing Out-of-Distribution Terrain
Xiaoyi Cai, James Queeney, Tong Xu +8
Self-supervised learning is a powerful approach for developing traversability models for off-road navigation, but these models often struggle with inputs unseen during training. Ex…