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stat.ML2026
Optimal Transport Meets Reinforcement Learning: A Survey
Yujie Zhu, Charles A. Hepburn, Matthew Thorpe +1
Reinforcement learning (RL) algorithms frequently compare probability distributions, such as state visitation distributions induced by policies and experts, action distributions fr…
stat.ML2024
State-Constrained Offline Reinforcement Learning
Charles A. Hepburn, Yue Jin, Giovanni Montana
Traditional offline reinforcement learning (RL) methods predominantly operate in a batch-constrained setting. This confines the algorithms to a specific state-action distribution p…
stat.ML2022
Model-based trajectory stitching for improved behavioural cloning and its applications
Charles A. Hepburn, Giovanni Montana
Behavioural cloning (BC) is a commonly used imitation learning method to infer a sequential decision-making policy from expert demonstrations. However, when the quality of the data…