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cs.LG2025
The Role of Environment Access in Agnostic Reinforcement Learning
Akshay Krishnamurthy, Gene Li, Ayush Sekhari
We study Reinforcement Learning (RL) in environments with large state spaces, where function approximation is required for sample-efficient learning. Departing from a long history…
cs.LG2023
When is Agnostic Reinforcement Learning Statistically Tractable?
Zeyu Jia, Gene Li, Alexander Rakhlin +2
We study the problem of agnostic PAC reinforcement learning (RL): given a policy class , how many rounds of interaction with an unknown MDP (with a potentially large state and a…