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This work proposes SkillGrain, a framework for learning reusable personalized skills from user feedback that decomposes feedback into independently actionable rules, predicts their transferability, and retains only those suitable for future requests.
Experiments and runtime validation show that AeroWeaver maintains valid skill execution under tested conditions and supports body-local multi-UAV operation without a central agent generating joint actions from global context, while reward-guided online updates provide a training-free path for adaptive learning swarm ag...
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