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Notes on skill selection
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SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents
Researchers present SkillGate, a method that aims to improve long-horizon agents' ability to select relevant skills during training. The current approach, outcome-rewarded Reinforcement Learning (RL), has limitations…
Task Decomposition-Guided Reranking for Adaptive Agent Skill Retrieval
The authors propose a method called SkillReranker to improve the ability of agent systems to complete complex tasks by accurately selecting skills from large libraries. The method involves semantic decomposition of…
Task Decomposition-Guided Reranking for Adaptive Agent Skill Retrieval
The authors propose a method called SkillReranker to improve the accuracy of selecting skills for complex tasks in agent systems. This is achieved by semantically decomposing both tasks and skills, creating a…
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