Harley Wiltzer
Research
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching.
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury
To appear at the International Conference on Learning Representations (ICLR), 2025Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning.
Harley Wiltzer*, Marc G. Bellemare, David Meger, Patrick Shafto, Yash Jhaveri*
Neural Information Processing Systems (NeurIPS), 2024Foundations of Multivariate Distributional Reinforcement Learning.
Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland
Neural Information Processing Systems (NeurIPS), 2024Simplifying Constraint Inference with Inverse Reinforcement Learning.
Adriana Hugessen, Harley Wiltzer, Glen Berseth
Neural Information Processing Systems (NeurIPS), 2024A Distributional Analogue to the Successor Representation.
Harley Wiltzer*, Jesse Farebrother*, Arthur Gretton, Yunhao Tang, Andre Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
International Conference on Machine Learning (ICML), 2024 Spotlight (top 3.5%)Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control.
Nate Rahn*, Pierluca D'Oro*, Harley Wiltzer, Pierre-Luc Bacon, Marc G. Bellemare
Neural Information Processing Systems (NeurIPS), 2023- Distributional Hamilton-Jacobi-Bellman Equations for
Continuous-Time Reinforcement Learning.
Harley Wiltzer, David Meger, Marc G. Bellemare
International Conference on Machine Learning (ICML), 2022 Spotlight - On the Evolution of Return Distributions in Continuous-Time
Reinforcement Learning.
M.Sc. Thesis.