SkillGate Mitigates Selector Credit Starvation in Long-Horizon Agents
August 18, 2026
SkillGate addresses selector credit starvation, where RL agents fail to learn skill selection because skill-naming tokens carry negligible loss in long trajectories. The method enables training policies to effectively select from procedural knowledge libraries during an episode.
HOW THIS AFFECTS YOU
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builderYou can build more reliable agents that effectively manage and retrieve large libraries of procedural skills.
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researcherThis identifies a specific structural failure mode in reinforcement learning for long-horizon task execution.