StateSkill-Agent: An Effective and Efficient Embodied Agent
Overview
StateSkill-Agent uses state-conditioned skill representation to model interactions as finite-state machines, enabling co-evolution of skills and model capabilities through StateGRPO. Experiments show effectiveness across various embodied tasks.
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- arXiv Robotics — research abstractsStateSkill-Agent: An Effective and Efficient Embodied Agent via State-conditioned Skill
This research proposes StateSkill, a new skill representation for embodied agents that models interactions as finite-state machines. The method integrates skill evolution and model optimization through StateGRPO, enabling co-evolution of skills and model capabilities. Extensive experiments validate the effectiveness of the approach across various embodied tasks.
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