The system uses a machine learning technique called attention-based map encoding, trained through reinforcement learning.

At UC Berkeley, researchers in Sergey Levine's Robotic AI and Learning Lab eyed a table where a tower of 39 Jenga blocks ...

Humans instinctively walk and run—brisk walking feels effortless, and we naturally adjust our stride and pace without ...

Discover how reinforcement learning is transforming quadruped robots like Spot into agile, adaptable tools for real-world applications.

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

Boston Dynamics' engineers push Spot to new limits, testing daring backflips to make the robot dog tougher and smarter.

The new reinforcement learning framework Teng and his colleagues developed could soon open new possibilities for the real-world deployment of legged robots.

News Release 13-Dec-2023 Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands Peer-Reviewed Publication Beijing Zhongke Journal Publising Co. Ltd.

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 ...

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 ...