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cs.LG2022
Optimistic PAC Reinforcement Learning: the Instance-Dependent View
Andrea Tirinzoni, Aymen Al-Marjani, Emilie Kaufmann
Optimistic algorithms have been extensively studied for regret minimization in episodic tabular MDPs, both from a minimax and an instance-dependent view. However, for the PAC RL pr…
cs.LG2022
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs
Andrea Tirinzoni, Aymen Al-Marjani, Emilie Kaufmann
In probably approximately correct (PAC) reinforcement learning (RL), an agent is required to identify an -optimal policy with probability . While minimax optimal algorithms…