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Found 2 papers, 1 papers with code
Parallel bootstrap-based on-policy deep reinforcement learning for continuous flow control applications
The coupling of deep reinforcement learning to numerical flow control problems has recently received a considerable attention, leading to groundbreaking results and opening new perspectives for the domain.
Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows
This research gauges the ability of deep reinforcement learning (DRL) techniques to assist the optimization and control of fluid mechanical systems.
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