Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control
We present the first application of an artificial neural network trained through a deep reinforcement learning agent to perform active flow control. It is shown that, in a two-dimensional simulation of the Kármán vortex street at moderate Reynolds number ( $Re=100$ ), our artificial neural network i...
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| Published in: | Journal of fluid mechanics Vol. 865; pp. 281 - 302 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Cambridge, UK
Cambridge University Press
25.04.2019
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| Subjects: | |
| ISSN: | 0022-1120, 1469-7645 |
| Online Access: | Get full text |
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