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.

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...

Recently, we interviewed Long Ouyang and Ryan Lowe, research scientists at OpenAI. As the creators of InstructGPT – one of the first major applications of reinforcement learning with human feedback ...

If you walk down the street shouting out the names of every object you see — garbage truck! bicyclist! sycamore tree! — most people would not conclude you are smart. But if you go through an obstacle ...

Machine learning (ML) might be considered the core subset of artificial intelligence (AI), and reinforcement learning may be the quintessential subset of ML that people imagine when they think of AI.

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...

Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by interacting with an environment. Unlike supervised learning, where ...

Physical AI has become one of the field’s biggest ambitions. These are machines that do more than generate text or images, ...