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stat.ML2026
Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahead
Corentin Pla, Hugo Richard, Marc Abeille +1
We study reinforcement learning (RL) with transition look-ahead, where the agent may observe which states would be visited upon playing any sequence of actions before decidi…
stat.ML2026
Minimax PAC Bounds for Learning in Exogenous Contextual MDPs
Corentin Pla, Hugo Richard, Marc Abeille +1
We study PAC learning in tabular discounted Markov decision processes with exogenous i.i.d. contexts, with discount factor , finite state space , action space $\math…
stat.ML2025
On the Hardness of Reinforcement Learning with Transition Look-Ahead
Corentin Pla, Hugo Richard, Marc Abeille +2
We study reinforcement learning (RL) with transition look-ahead, where the agent may observe which states would be visited upon playing any sequence of actions before decidi…