An Optimistic Posterior Sampling Strategy for Bayesian Reinforcement Learning
By Raphael Fonteneau, N. Korda, R´emi Munos. 2013
13 citations recorded by the source corpus.
How researchers see this paper
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- Ian Osband
- Benjamin Van Roy
- Brendan O'Donoghue
- Sergey Levine
- Chi Jin
- Daniel Russo
- Yuxi Li
- Pieter Abbeel
Citations in the corpus
- Why is Posterior Sampling Better than Optimism for Reinforcement Learning? (2016, methodology): “We believe that an important difference is that PSRL, unlike Thompson sampling, should not resample every timestep but previous implementations had compared to this faulty benchmark [10].”