AZoOptics

Researchers Design AI-Driven Photonic Crystal Fiber Modulator

A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...

Quantori MLConfGen Wins “Machine Learning Innovation Award” in 2026 AI Breakthrough Awards Program

Ninth Annual Program Honors the AI Innovators Shaping the Next Era of Global InnovationCAMBRIDGE, Mass.--(BUSINESS WIRE)--#AIBreakthroughAwards--Quantori, a leading provider of digital transformation ...
Aerospace and Mechanical Insider on MSN

Multi-agent reinforcement learning driving smart factory agility

At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...
IEEE

Q-Advantage Integrated Human-Guided Reinforcement Learning for Safe End-to-End Autonomous Driving

Abstract: Reinforcement learning (RL) is a promising approach for end-to-end autonomous driving, but its practical deployment remains challenging due to low sample efficiency and sensitivity to reward ...
Microsoft

In-Context Compositional Q-Learning for Offline Reinforcement Learning

Accurately estimating the Q-function is a central challenge in offline reinforcement learning. However, existing approaches often rely on a single global Q-function, which struggles to capture the ...
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 ...
Scientific Research Publishing

Kostrikov, I., Nair, A. and Levine, S. (2021) Offline Reinforcement Learning with Implicit Q-Learning. arXiv: 2110.06169.

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...
Scientific Research Publishing

Kumar, A., Zhou, A., Tucker, G. and Levine, S. (2020) Conservative Q-Learning for Offline Reinforcement Learning. Advances in Neural Information Processing Systems, 33, 1179-1191.

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...
The Conversation

What is reinforcement learning? An AI researcher explains a key method of teaching machines – and how it relates to training your dog

Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a cornerstone of intelligence for machines and living ...