As reinforcement learning matures, it's likely to become a foundational element of intelligent robotics, enabling systems that are not just automated, but truly autonomous.

We present Multiple Scenario Verifiable Reinforcement Learning via Policy Extraction (MSVIPER), a new method for policy distillation to decision trees for improved robot navigation. MSVIPER learns an ...

A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater ...

Reinforcement learning techniques could be the keys to integrating robots — who use machine learning to output more than words — into the real world.

Indeed, with reinforcement learning, robots will be able to take on even more “human” qualities of discernment and complex decision-making.

To this end, reinforcement learning has been particularly useful with robotics. For example, OpenAI has used this technique for a robotic arm that was able to solve the Rubik’s cube.

A group of Google researchers have built a robot capable of learning to walk by itself with minimal human intervention. The researchers used a kind of AI called deep reinforcement learning to ...

Tesla is ramping up hiring for its humanoid robot program, Optimus, including some reinforcement learning engineers. It was hard to take Tesla Bot seriously when Elon Musk announced it by having ...