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 ...
VentureBeat

Beyond math and coding: New RL framework helps train LLM agents for complex, real-world tasks

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...
Morningstar

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 ...
InfoWorld

How multi-agent collaboration is redefining real-world problem solving

When I first started working with multi-agent collaboration (MAC) systems, they felt like something out of science fiction. It’s a group of autonomous digital entities that negotiate, share context, ...