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cs.LG2022
An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy +1
We study a posterior sampling approach to efficient exploration in constrained reinforcement learning. Alternatively to existing algorithms, we propose two simple algorithms that a…
cs.LG2022
The Impact of Batch Learning in Stochastic Linear Bandits
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy +1
We consider a special case of bandit problems, named batched bandits, in which an agent observes batches of responses over a certain time period. Unlike previous work, we consider…