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20152024
most citedArtificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control

572 citations · 2.1k across the 54 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…