VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents 事件

VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents arXiv:2606.05395v1 Announce Type: cross Abstract: Reusable robot skills are becoming the basic units through which embodied agents turn open-ended instructions into long-horizon physical behavior. We argue that, while foundation models have collapsed the cost of creating these skills, the cost of trusting them has not. Existing skill-evolution loops refine skills through execution feedback, unit tests, environment reward, or