CoSkill: Joint Reinforcement Learning of Reasoning and Meta-Skill Agents for Hierarchical Skill Evolution

TL;DR - CoSkill is a multi-agent reinforcement learning framework that jointly trains an LLM reasoning agent and a learnable meta-skill agent over a hierarchical skill library. This co-adaptation improves sample efficiency, task performance, and wall-clock efficiency compared with prior skill-based and RL baselines.

• The reasoning and meta-skill agents operate cooperatively using a shared model backbone.
• The reasoning agent uses a retrieved task skill and selected child step skills, while task outcomes guide the meta-skill agent in refining those steps.
• CoSkill replaces fixed meta-skill workflows with a learned agent, enabling end-to-end skill evolution alongside policy optimization.
• It achieves 98.4% success on ALFWorld and 90.6% on WebShop, improving over prior baselines by 3.5 and 6.2 percentage points, respectively.