Tech Xplore on MSN

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
Physics World

Reinforcement learning could help airborne wind energy take off

Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...
Devdiscourse

AI can cut emissions and congestion in urban transport by nearly 50%

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

Will Reinforcement Learning Take Us To AGI?

Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...
Deep Learning with Yacine on MSN

Watch an AI learn to balance a stick — reinforcement learning in action

Watch an AI agent learn how to balance a stick—completely from scratch—using reinforcement learning! This project walks you ...
Forbes

The Rise And Rise Of Reinforcement Learning: AI’s Quiet Revolution

Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...
Nature

Multi-Agent Reinforcement Learning

Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...
Electronics360

Wind turbine control systems: From PID to reinforcement learning

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

Reinforcement learning improves behaviour from evaluative feedback

Reinforcement-learning algorithms 1,2 are inspired by our understanding of decision making in humans and other animals in which learning is supervised through the use of reward signals in response to ...