MorphAgent: Empowering Agents through Self-Evolving Profiles and Decentralized Collaboration

• URL: http://arxiv.org/abs/2410.15048v1
• Date: Sat, 19 Oct 2024 09:10:49 GMT
• Title: MorphAgent: Empowering Agents through Self-Evolving Profiles and Decentralized Collaboration
• Authors: Siyuan Lu, Jiaqi Shao, Bing Luo, Tao Lin,
• Abstract summary: This paper introduces MorphAgent, a novel framework for decentralized multi-agent collaboration. MorphAgent employs self-evolving agent profiles, optimized through three key metrics. Our experimental results show that MorphAgent outperforms traditional static-role MAS in terms of task performance and adaptability to changing requirements.
• Score: 8.078098082305575
• License:
• Abstract: Large Language Model (LLM) based multi-agent systems (MAS) have shown promise in tackling complex tasks, but often rely on predefined roles and centralized coordination, limiting their adaptability to evolving challenges. This paper introduces MorphAgent, a novel framework for decentralized multi-agent collaboration that enables agents to dynamically evolve their roles and capabilities. Our approach employs self-evolving agent profiles, optimized through three key metrics, guiding agents in refining their individual expertise while maintaining complementary team dynamics. MorphAgent implements a two-phase process: a warm-up phase for initial profile optimization, followed by a task execution phase where agents continuously adapt their roles based on task feedback. Our experimental results show that MorphAgent outperforms traditional static-role MAS in terms of task performance and adaptability to changing requirements, paving the way for more robust and versatile multi-agent collaborative systems. Our code will be publicly available at \url{https://github.com/LINs-lab/learn2collaborate}.

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