18 citations · 31 across the 6 of their papers we have counts for
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cs.LG2021
Exploration and Incentives in Reinforcement Learning
Max Simchowitz, Aleksandrs Slivkins
How do you incentivize self-interested agents to when they prefer to ? We consider complex exploration problems, where each agent faces the sam…
cs.LG2020★ 13 cited
Constrained episodic reinforcement learning in concave-convex and knapsack settings
Kianté Brantley, Miroslav Dudik, Thodoris Lykouris +4
We propose an algorithm for tabular episodic reinforcement learning with constraints. We provide a modular analysis with strong theoretical guarantees for settings with concave rew…
cs.LG2019★ 18 cited
Corruption-robust exploration in episodic reinforcement learning
Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins +1
We initiate the study of multi-stage episodic reinforcement learning under adversarial corruptions in both the rewards and the transition probabilities of the underlying system ext…