Dynamic Dual-Granularity Skill Bank for Agentic RL

This paper introduces a novel approach to reinforcement learning by proposing a dynamic dual-granularity skill bank, designed to enhance the capabilities of AI agents in complex environments. It focuses on developing agentic reinforcement learning solutions that can leverage skills at varying levels of abstraction.