14 citations · 58 across the 23 of their papers we have counts for
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cs.LG2023
Towards Minimax Optimality of Model-based Robust Reinforcement Learning
Pierre Clavier, Erwan Le Pennec, Matthieu Geist
We study the sample complexity of obtaining an -optimal policy in \emph{Robust} discounted Markov Decision Processes (RMDPs), given only access to a generative model of the nomi…
cs.LG2022★ 2 cited
Robust Reinforcement Learning with Distributional Risk-averse formulation
Pierre Clavier, Stéphanie Allassonière, Erwan Le Pennec
Robust Reinforcement Learning tries to make predictions more robust to changes in the dynamics or rewards of the system. This problem is particularly important when the dynamics an…