On Friday, researchers from Nvidia, UPenn, Caltech, and the University of Texas at Austin announced Eureka, an algorithm that uses OpenAI’s GPT-4 language model for designing training goals (called ...

Legged robots, which are often inspired by animals and insects, could help humans to complete various real-world tasks, for instance delivering parcels or monitoring specific environments. In recent ...

Deepreinforcement learning has disadvantages such as low sample utilization and slow convergence, and thousandsof trial-and-error iterations are required to perform ...

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 ...

US robotics firm Figure has made significant progress in developing a natural humanoid walking motion using reinforcement learning. A new video released by the firm showcases its humanoid robots ...

What if robots could learn to adapt to their surroundings as effortlessly as humans do? The rise of quadruped robots, like Boston Dynamics’ Spot, is turning this vision into reality. By integrating ...

Unity Technologies has linked its game engine to machine learning software, in order to train better virtual characters and physical robots. For years, video game developers have used artificial ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...