Deep reinforcement learning (DRL) has emerged as a transformative approach in the realm of fluid dynamics, offering a data-driven framework to tackle the intrinsic complexities of active flow control.

Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

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 on, ...

Have you ever wished AI could truly understand the complexities of your field—not just replicate data but reason through intricate, domain-specific challenges? Whether you’re a researcher analyzing ...