Nature

Asymmetric reinforcement learning facilitates human inference of transitive relations

Humans and other animals are capable of inferring never-experienced relations (for example, A > C) from other relational observations (for example, A > B and B > C). The processes behind such ...
Nature

A Primer on Reinforcement Learning in Medicine for Clinicians

In healthcare, making the right decisions is crucial, as professionals face complex choices daily, from diagnosis to treatment planning and resource allocation. Patient care needs strategies that ...
Forbes

The Autonomous Advantage: Reinforcement Learning’s Role In The Next Era Of AI

The age of truly autonomous artificial intelligence, where systems proactively learn, adapt and optimize amid real-world complexities instead of simply reacting, has been a long-held aspiration. Now, ...
Singularity Hub

Quantum Computing and Reinforcement Learning Are Joining Forces to Make Faster AI

Deep reinforcement learning is having a superstar moment. Powering smarter robots. Simulating human neural networks. Trouncing physicians at medical diagnoses and crushing humanity’s best gamers at Go ...
Geeky Gadgets

Watch AI learn to walk using Deep Reinforcement Learning (DRL)

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...
Physics World

The pros and cons of reinforcement learning in physical science

Machines that learn like babies: Reinforcement learning expert David Silver speaking at the Heidelberg Laureate Forum on 15 September, 2025. (Courtesy: Bernhard Kreutzer/HLF) Today’s artificial ...
Microsoft

With reinforcement learning, Microsoft brings a new class of AI solutions to customers

Someone looking to book a vacation online today might have very different preferences than they did before the COVID-19 pandemic. Instead of flying to an exotic beach, they might feel more comfortable ...