Updated Jan 2025
For the most up-to-date list of publications, please visit my Google Scholar page.
Preprints
GRAM: Generalization in deep RL with a robust adaptation module
James Queeney, Xiaoyi Cai, Mouhacine Benosman, Jonathan P. How
arXiv preprint, 2024
Provably efficient off-policy adversarial imitation learning with convergence guarantees
Yilei Chen, Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis
arXiv preprint, 2024
Peer-Reviewed Publications
Visually robust adversarial imitation learning from videos with contrastive learning
Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis
To appear in IEEE International Conference on Robotics and Automation, 2025 (ICRA 2025)
PIETRA: Physics-informed evidential learning for traversing out-of-distribution terrain
Xiaoyi Cai, James Queeney, Tong Xu, Aniket Datar, Chenhui Pan, Max Miller, Ashton Flather, Philip R. Osteen, Nicholas Roy, Xuesu Xiao, Jonathan P. How
IEEE Robotics and Automation Letters, 2025 (RA-L)
Generalized policy improvement algorithms with theoretically supported sample reuse
James Queeney, Ioannis Ch. Paschalidis, Christos G. Cassandras
IEEE Transactions on Automatic Control, 2025 (TAC)
A model-based approach for improving reinforcement learning efficiency leveraging expert observations
Erhan Can Ozcan, Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis
IEEE Conference on Decision and Control, 2024 (CDC 2024)
Adversarial imitation learning from visual observations using latent information
Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis
Transactions on Machine Learning Research, 2024 (TMLR)
Optimal transport perturbations for safe reinforcement learning with robustness guarantees
James Queeney, Erhan Can Ozcan, Ioannis Ch. Paschalidis, Christos G. Cassandras
Transactions on Machine Learning Research, 2024 (TMLR)
Risk-averse model uncertainty for distributionally robust safe reinforcement learning
James Queeney, Mouhacine Benosman
Advances in Neural Information Processing Systems, 2023 (NeurIPS 2023)
Opportunities and challenges from using animal videos in reinforcement learning for navigation
Vittorio Giammarino, James Queeney, Lucas C. Carstensen, Michael E. Hasselmo, Ioannis Ch. Paschalidis
22nd IFAC World Congress, 2023 (IFAC 2023)
Generalized proximal policy optimization with sample reuse
James Queeney, Ioannis Ch. Paschalidis, Christos G. Cassandras
Advances in Neural Information Processing Systems, 2021 (NeurIPS 2021)
Uncertainty-aware policy optimization: A robust, adaptive trust region approach
James Queeney, Ioannis Ch. Paschalidis, Christos G. Cassandras
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 (AAAI 2021)
Dissertation
Reliable deep reinforcement learning: Stable training and robust deployment
James Queeney
PhD thesis, Boston University, 2023
