Reinforcement-learning algorithms 1,2 are inspired by our understanding of decision making in humans and other animals in which learning is supervised through the use of reward signals in response ...

What is reinforcement learning? There are three kinds of machine learning: unsupervised learning, supervised learning, and reinforcement learning. Each of these is good at solving a different set ...

Reinforcement learning (RL) is a branch of machine learning that addresses problems where there is no explicit training data. Q-learning is an algorithm that can be used to solve some types of RL ...

An algorithm that learns through rewards may show how our brain does too By optimizing reinforcement-learning algorithms, DeepMind uncovered new details about how dopamine helps the brain learn.

The framework is detailed in the survey paper " Survey of recent multi-agent reinforcement learning algorithms utilizing centralized training," which is featured in the SPIE Digital Library.

Reinforcement learning (RL) is a powerful type of AI technology that can learn strategies to optimally control large, complex systems.

David Silver ¹², Thomas Hubert ¹, Julian Schrittwieser ¹, Ioannis Antonogloux ¹, Matthew Lai ¹, Arthur Guez ¹, Marc Lanctot ¹, Laurent Sifre ¹, Dharshan Kumaran ¹, Thore Graepel ¹, Timothy Lillicrap ¹ ...