With growing capabilities of large language models (LLMs) comes growing affordances for human-like and context-aware conversational partners. On from this, some recent work has investigated the use of LLMs to simulate multiple conversational partners, such as to assist users with problem solving or to simulate an environment populated entirely with LLMs. Beyond this, we are interested in discussing and exploring the use of LLMs to simulate multiple personas to assist and augment users in educational settings that could benefit from multiple interlocutors. We discuss prior work that uses LLMs to simulate multiple personas sharing the same environment, and discuss example scenarios where multiple conversational agent partners could be used in education.

翻译：随着大语言模型（LLM）能力的不断增强，其模拟类人且具备上下文感知能力的对话伙伴的潜在功能也日益显著。基于此，近期一些研究开始探索利用LLM模拟多个对话伙伴，例如协助用户解决问题或构建完全由LLM组成的模拟环境。此外，我们进一步关注并探讨如何利用LLM模拟多个角色，在需要多对话方参与的教育场景中辅助和增强用户学习。本文回顾了利用LLM模拟共享同一环境的多个角色的相关先前工作，并讨论了在教学中运用多对话智能体伙伴的示例场景。