Abstract: High precision control of soft robots is challenging due to their stohcastic behavior and material-dependent nature. While RL has been applied in soft robotics, achieving precision in task ...

An overview of our research on agentic RL. In this work, we systematically investigate three dimensions of agentic RL: data, algorithms, and reasoning modes. Our findings reveal: Real end-to-end ...

Britain produced a record-high amount of electricity from renewable energy last year, a study revealed on Friday. Britain is ...

PRIME-RL is a framework for large-scale asynchronous reinforcement learning. It is designed to be easy-to-use and hackable, yet capable of scaling to 1000+ GPUs. Beyond that, here is why we think you ...

Abstract: Long-range indoor navigation requires guiding robots with noisy sensors and controls through cluttered environments along paths that span a variety of buildings. We achieve this with PRM-RL, ...