Nature

Deep Reinforcement Learning for Active Flow Control

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.
Forbes

From Turing To DeepSeek, Reinforcement Learning Soars To AI Summit

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
EurekAlert!

Deep reinforcement learning optimizes distributed manufacturing scheduling

A recent study published in Engineering presents a significant advancement in manufacturing scheduling. Researchers Xueyan Sun, Weiming Shen, Jiaxin Fan, and their colleagues from Huazhong University ...
Time

Reinforcement Learning

This article is published by AllBusiness.com, a partner of TIME. What is "Reinforcement Learning"? Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by ...
VentureBeat

DeepSeek-R1’s bold bet on reinforcement learning: How it outpaced OpenAI at 3% of the cost

DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...
AZoRobotics on MSN

Simulation-Only Training Enables Quadruped Robots to Master Real-World Terrain

A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...
Interesting Engineering on MSN

AI-trained quadruped robot walks rough, low-friction terrain without human input

A quadruped robot has learned to walk across slippery, uneven terrain entirely through simulation, ...