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.

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...

Schematic diagram of the NOEO-based photonic accelerator. (a) Experimental setup of the NOEO. (b) Evolution of the temporal sequences generated by the NOEO with an increasing net gain β. (c) MAB ...

Picture this: a self-driving car smoothly navigating treacherous mountain roads with consecutive hairpin turns – a scenario that would challenge even the most experienced human drivers. This vision is ...

A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and adaptive locomotion in simulation.