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2023

Experiential Co-Learning of Software-Developing Agents

Qian, Chen, Dang, Yufan, Li, Jiahao et al.

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Recent advancements in large language models (LLMs) have brought significant changes to various domains, especially through LLM-driven autonomous agents.

A representative scenario is in software development, where LLM agents demonstrate efficient collaboration, task division, and assurance of software quality, markedly reducing the need for manual involvement.
However, these agents frequently perform a variety of tasks independently, without benefiting from past experiences, which leads to repeated mistakes and inefficient attempts in multi-step task execution.
To this end, we introduce Experiential Co-Learning, a novel LLM-agent learning framework in which instructor and assistant agents gather shortcut-oriented experiences from their historical trajectories and use these past experiences for future task execution.

Experiential Co-Learning of Software-Developing Agents · Around

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