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stat.ML2026
Action-Free Offline-to-Online RL via Discretised State Policies
Natinael Solomon Neggatu, Jeremie Houssineau, Giovanni Montana
Most existing offline RL methods presume the availability of action labels within the dataset, but in many practical scenarios, actions may be missing due to privacy, storage, or s…
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…