218 citations · 811 across the 15 of their papers we have counts for
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physics.comp-ph2019★ 108 cited
A review on Deep Reinforcement Learning for Fluid Mechanics
Paul Garnier, Jonathan Viquerat, Jean Rabault +3
Deep reinforcement learning (DRL) has recently been adopted in a wide range of physics and engineering domains for its ability to solve decision-making problems that were previousl…
physics.comp-ph2019★ 218 cited
Accelerating Deep Reinforcement Learning strategies of Flow Control through a multi-environment approach
Jean Rabault, Alexander Kuhnle
Deep Reinforcement Learning (DRL) has recently been proposed as a methodology to discover complex Active Flow Control (AFC) strategies [Rabault, J., Kuchta, M., Jensen, A., Reglade…