CGMI：可配置的通用多智能体交互框架
CGMI: Configurable General Multi-Agent Interaction Framework
AI总结：
针对大语言模型智能体领域知识不足、缺乏有效认知架构的问题，提出CGMI框架，通过树形人格管理方法和基于ACT*模型的带技能库认知架构，实现高真实感的多智能体交互模拟，课堂仿真效果贴近真实场景且将开源。
摘要：
受益于大语言模型（LLMs）的强大能力，基于LLM的智能体已展现出解决特定领域任务和模拟人类行为的潜力。然而，由于这些智能体的领域专业知识有限，且缺乏有效的认知架构，其生成的内容仍略显肤浅。为解决这一问题，我们提出了可配置通用多智能体交互（CGMI）框架，旨在复现真实场景中的人类交互。具体而言，我们提出了一种树形结构的方法，用于智能体人格的分配、检测与维持。此外，我们基于ACT*模型设计了配备技能库的认知架构，该架构包含记忆、反思和规划模块。我们还集成了通用智能体以增强虚拟环境的真实感。利用CGMI框架，我们模拟了大量师生课堂互动。实验表明，教学方法、课程设置和学生表现等方面都与真实课堂场景高度相似。我们将开源本研究工作。
英文摘要：
Benefiting from the powerful capabilities of large language models (LLMs), agents based on LLMs have shown the potential to address domain-specific tasks and emulate human behaviors. However, the content generated by these agents remains somewhat superficial, owing to their limited domain expertise and the absence of an effective cognitive architecture. To address this, we present the Configurable General Multi-Agent Interaction (CGMI) framework, designed to replicate human interactions in real-world scenarios. Specifically, we propose a tree-structured methodology for the assignment, detection, and maintenance of agent personality. Additionally, we designed a cognitive architecture equipped with a skill library based on the ACT* model, which contains memory, reflection, and planning modules. We have also integrated general agents to augment the virtual environment's realism. Using the CGMI framework, we simulated numerous classroom interactions between teacher and students. The experiments indicate that aspects such as the teaching methodology, curriculum, and student performance closely mirror real classroom settings. We will open source our work.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
