The American Journal of Managed Care

Offline Reinforcement Learning Improves Time in Range via Hybrid Closed-Loop Systems

This form of reinforcement learning was also shown to correct for control scenarios like irregular meal timing and compression errors. Offline reinforcement learning (RL) in hybrid closed-loop systems ...

Reinforcement learning and organizational management

Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...
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

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

The Importance Of Evaluation In The Reinforcement Learning Revolution

David Shan is the Co-Founder and CTO of Clado, who trains in-house small language models to build the best people search algorithm. We celebrate RL breakthroughs, but behind the hype lies a brittle ...
FOX8 Cleveland

Imubit Launches Optimizing Brain™ Solution: The Process Industry's First Closed Loop AI Optimization Solution Powered by Reinforcement Learning

Houston, Sept. 18, 2024 (GLOBE NEWSWIRE) -- Imubit Launches Optimizing Brain™ Solution: The Process Industry’s First Closed Loop AI Optimization Solution Powered by Reinforcement Learning Houston, TX ...
ZDNet

True agentic AI is years away - here's why and how we get there

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.