Experiential Co-Learning of Software-Developing Agents

التفاصيل البيبلوغرافية
العنوان: Experiential Co-Learning of Software-Developing Agents
المؤلفون: Qian, Chen, Dang, Yufan, Li, Jiahao, Liu, Wei, Xie, Zihao, Wang, Yifei, Chen, Weize, Yang, Cheng, Cong, Xin, Che, Xiaoyin, Liu, Zhiyuan, Sun, Maosong
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Software Engineering
الوصف: 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. The extensive experiments demonstrate that the framework enables agents to tackle unseen software-developing tasks more effectively. We anticipate that our insights will guide LLM agents towards enhanced autonomy and contribute to their evolutionary growth in cooperative learning. The code and data are available at https://github.com/OpenBMB/ChatDev.
Comment: Accepted to ACL 2024, https://github.com/OpenBMB/ChatDev
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2312.17025
رقم الأكسشن: edsarx.2312.17025
قاعدة البيانات: arXiv