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Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
28 September 2022
D. Tiapkin
Denis Belomestny
Daniele Calandriello
Eric Moulines
Rémi Munos
A. Naumov
Mark Rowland
Michal Valko
Pierre Menard
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Papers citing
"Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees"
2 / 2 papers shown
Title
Provably Efficient Exploration in Constrained Reinforcement Learning:Posterior Sampling Is All You Need
Danil Provodin
Pratik Gajane
Mykola Pechenizkiy
M. Kaptein
17
0
0
27 Sep 2023
UCB Momentum Q-learning: Correcting the bias without forgetting
Pierre Menard
O. D. Domingues
Xuedong Shang
Michal Valko
72
40
0
01 Mar 2021
1