Active flow control using deep reinforcement learning with time delays in Markov decision process and autoregressive policy

Classical active flow control (AFC) methods based on solving the Navier–Stokes equations are laborious and computationally intensive even with the use of reduced-order models. Data-driven methods offer a promising alternative for AFC, and they have been applied successfully to reduce the drag of two...

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