This research project investigates the application of Deep Reinforcement Learning (DRL) for active flow control around a confined square cylinder. By combining Computational Fluid Dynamics (CFD) ...

Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative ... SMARTs evaluate flow-chart-like treatment ...

Such agents are built with the help of a paradigm of machine learning called “Reinforcement Learning” (RL). In this course, you’ll walk through different approaches to RL. You’ll move from a simple ...

The complexity and uncertainty in power systems leads to a great challenge for controlling the power grid using traditional manual adjustment methods. Reinforcement learning is a promising data-driven ...

Mixing things up: Optimizing fluid mixing with machine learning. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2022 / 08 / 220829112806.htm ...

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades ...