EurekAlert!

A graph reinforcement learning framework for real-time distributed multi-robot task allocation

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
KTLA

AgiBot Achieves First Real-World Deployment of Reinforcement Learning in Industrial Robotics

SHANGHAI, Nov. 2, 2025 /PRNewswire/ -- AgiBot, a robotics company specializing in embodied intelligence, announced a key milestone with the successful deployment of its Real-World Reinforcement ...
Gizmochina

AgiBot Makes History: First Robot to Learn Directly on the Factory Floor

AgiBot, a robotics company focused on embodied intelligence, has achieved a major milestone by successfully deploying its Real-World Reinforcement Learning (RW-RL) system on a pilot production line ...
The Next Web

Everything you need to know about model-free and model-based reinforcement learning

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.
Science Daily

Advanced universal control system may revolutionize lower limb exoskeleton control and optimize user experience

A team of researchers has developed a new method for controlling lower limb exoskeletons using deep reinforcement learning. The method enables more robust and natural walking control for users of ...

Manulife Financial Corporation: Manulife Selects Adaptive ML as Reinforcement Learning Engine to Scale Enterprise AI

Partnership accelerates progress on Manulife's proprietary AI platform with real-time model optimization TORONTO and NEW YORK, Dec. 22, 2025 /PRNewswire/ -- Manulife announced today that it ...