SkillFlow: Efficient Skill and Code Transfer Through Communication in Adapting AI Agents

• URL: http://arxiv.org/abs/2504.06188v1
• Date: Tue, 08 Apr 2025 16:33:24 GMT
• Title: SkillFlow: Efficient Skill and Code Transfer Through Communication in Adapting AI Agents
• Authors: Pagkratios Tagkopoulos, Fangzhou Li, Ilias Tagkopoulos,
• Abstract summary: SkillFlow is a technology-agnostic framework that allows agents to expand their functionality in an ad-hoc fashion.<n>We show that SkillFlow's ability to accelerate task completion and lead to lower cumulative costs in a real-world application.
• Score: 1.249418440326334
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: AI agents are autonomous systems that can execute specific tasks based on predefined programming. Here, we present SkillFlow, a modular, technology-agnostic framework that allows agents to expand their functionality in an ad-hoc fashion by acquiring new skills from their environment or other agents. We present a theoretical model that examines under which conditions this framework would be beneficial, and we then explore SkillFlow's ability to accelerate task completion and lead to lower cumulative costs in a real-world application, namely scheduling agents for calendar events. We demonstrate that within a few iterations, SkillFlow leads to considerable (24.8%, p-value = $6.4\times10^{-3}$) gains in time and cost, especially when the communication cost is high. Finally, we draw analogies from well-studied biological systems and compare this framework to that of lateral gene transfer, a significant process of adaptation and evolution in novel environments.

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