James Queeney

James Queeney
  • Biography

    Jimmy conducts research on data-driven methods for decision making and control. During his PhD, he developed reliable deep reinforcement learning algorithms with guarantees on training stability, robustness, and safety.

  • MERL Publications

    •  Queeney, J., Benosman, M., "Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning", arXiv, January 2023.
      BibTeX arXiv
      • @article{Queeney2023jan,
      • author = {Queeney, James and Benosman, Mouhacine},
      • title = {Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning},
      • journal = {arXiv},
      • year = 2023,
      • month = jan,
      • url = {https://arxiv.org/abs/2301.12593}
      • }
  • Other Publications

    •  Vittorio Giammarino, James Queeney, Lucas C. Carstensen, Michael E. Hasselmo and Ioannis Ch. Paschalidis, "Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation", 22nd IFAC World Congress, 2023.
      BibTeX
      • @Inproceedings{giammarino_2023_ifac,
      • author = {Giammarino, Vittorio and Queeney, James and Carstensen, Lucas C. and Hasselmo, Michael E. and Paschalidis, Ioannis Ch.},
      • title = {Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation},
      • booktitle = {22nd IFAC World Congress},
      • year = 2023
      • }
    •  Vittorio Giammarino, James Queeney and Ioannis Ch. Paschalidis, "Adversarial Imitation Learning from Visual Observations using Latent Information", 2023.
      BibTeX
      • @Misc{giammarino_2023_laifo,
      • author = {Giammarino, Vittorio and Queeney, James and Paschalidis, Ioannis Ch.},
      • title = {Adversarial Imitation Learning from Visual Observations using Latent Information},
      • year = 2023
      • }
    •  James Queeney, "Reliable Deep Reinforcement Learning: Stable Training and Robust Deployment", 2023, Boston University.
      BibTeX
      • @Phdthesis{queeney_2023_dissertation,
      • author = {Queeney, James},
      • title = {Reliable Deep Reinforcement Learning: Stable Training and Robust Deployment},
      • school = {Boston University},
      • year = 2023
      • }
    •  James Queeney, Erhan Can Ozcan, Ioannis Ch. Paschalidis and Christos G. Cassandras, "Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees", 2023.
      BibTeX
      • @Misc{queeney_2023_otp,
      • author = {Queeney, James and Ozcan, Erhan Can and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
      • title = {Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees},
      • year = 2023
      • }
    •  James Queeney and Mouhacine Benosman, "Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning", Advances in Neural Information Processing Systems, 2023, vol. 36.
      BibTeX
      • @Inproceedings{queeney_2023_ramu,
      • author = {Queeney, James and Benosman, Mouhacine},
      • title = {Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning},
      • booktitle = {Advances in Neural Information Processing Systems},
      • year = 2023,
      • volume = 36,
      • publisher = {Curran Associates, Inc.}
      • }
    •  James Queeney, Ioannis Ch. Paschalidis and Christos G. Cassandras, "Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse", 2022.
      BibTeX
      • @Misc{queeney_2022_gpi,
      • author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
      • title = {Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse},
      • year = 2022
      • }
    •  James Queeney, Ioannis Ch. Paschalidis and Christos G. Cassandras, "Generalized Proximal Policy Optimization with Sample Reuse", Advances in Neural Information Processing Systems, 2021, vol. 34.
      BibTeX
      • @Inproceedings{queeney_2021_geppo,
      • author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
      • title = {Generalized Proximal Policy Optimization with Sample Reuse},
      • booktitle = {Advances in Neural Information Processing Systems},
      • year = 2021,
      • volume = 34,
      • publisher = {Curran Associates, Inc.}
      • }
    •  James Queeney, Ioannis Ch. Paschalidis and Christos G. Cassandras, "Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach", Proceedings of the AAAI Conference on Artificial Intelligence, 2021, vol. 35, pp. 9377-9385.
      BibTeX
      • @Inproceedings{queeney_2021_uatrpo,
      • author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
      • title = {Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach},
      • booktitle = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
      • year = 2021,
      • volume = 35,
      • pages = {9377--9385},
      • publisher = {{AAAI} Press}
      • }