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, ...

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 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.

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 ...

Progress in self-­driving cars and other forms of automation will slow dramatically unless machines can hone skills through experience. Inside a simple computer simulation, a group of self-driving ...

In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...

It was not long ago that the world watched World Chess Champion Garry Kasparov lose a decisive match against a supercomputer. IBM’s Deep Blue embodied the state of the art in the late 1990s, when a ...

The near-term feasibility of self-driving cars depends on the limits of current machine learning approaches. This article is about using reinforcement learning to solve path planning and driving ...

Reinforcement Learning, an artificial intelligence approach, has the potential to guide physicians in designing sequential treatment strategies for better patient outcomes but requires significant ...