Reinforcement learning (RL) represents a paradigm shift in process control, offering adaptive and data‐driven strategies for the management and optimisation of complex industrial processes. By ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

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 ...

AI can help develop methods of locomotion that are unconventional but fast AI can help develop methods of locomotion that are unconventional but fast is a senior reporter who has covered AI, robotics, ...

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

The companies have jointly developed an AI robot control system that can interact with the physical world and be used in various fields from logistics to rescue operations. Tests have shown that in ...

This multi-objective setup encourages natural walking behavior rather than rigid or inefficient movement. A four-stage ...

PNDbotics unveils Adam-U Ultra, a humanoid robot with VLA AI and 10,000+ data samples, learning new skills in hours.

A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...

Boasting a sophisticated design tailored for versatile mobility, Cassie demonstrates remarkable agility as it effortlessly navigates quarter-mile runs and performs impressive long jumps without ...

Breakthroughs, discoveries, and DIY tips sent six days a week. Terms of Service and Privacy Policy. Researchers are training robots to perform an ever-growing number ...