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cs.LG2026
Towards Generalisable Imitation Learning Through Conditioned Transition Estimation and Online Behaviour Alignment
Nathan Gavenski, Matteo Leonetti, Odinaldo Rodrigues
State-of-the-art imitation learning from observation methods (ILfO) have recently made significant progress, but they still have some limitations: they need action-based supervised…
cs.LG2025
Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning
Roberto Cipollone, Luca Iocchi, Matteo Leonetti
The main focus of Hierarchical Reinforcement Learning (HRL) is studying how large Markov Decision Processes (MDPs) can be more efficiently solved when addressed in a modular way, b…