面向元宇宙服务生态中LLM赋能智能体的可解释情感对齐框架
An Explainable Emotion Alignment Framework for LLM-Empowered Agent in Metaverse Service Ecosystem
- College of Intelligence and Computing（智能与计算学院）
- Tianjin University（天津大学）
- Tianjin Key Laboratory of Healhy Habitat and Smart Technology（天津健康人居环境与智能技术重点实验室）
- Laboratory of Computation and Analytics of Complex Management Systems（复杂管理系统计算与分析实验室）
- Faculty of Environment, Science and Economy（环境、科学与经济学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对元宇宙服务生态中LLM智能体衔接虚实服务存在的数据融合、知识关联及伦理安全等问题，提出可解释情感对齐框架，将事实因素融入决策循环实现事实对齐，经外卖场景仿真验证可产生更真实的社会涌现效果。
AI中文摘要：
元宇宙服务是元宇宙与服务系统融合的产物，旨在解决元宇宙内数字化身、数字孪生和数字原生代相关的服务类挑战。随着大语言模型（LLM）的兴起，智能体如今在元宇宙服务生态中扮演核心角色，承担双重功能：既作为代表虚拟世界中用户的数字化身，也作为提供个性化支持的服务助手（或NPC）。然而，在元宇宙服务生态的建模过程中，现有基于LLM的智能体在衔接虚拟世界服务与现实世界服务方面面临重大挑战，尤其体现在角色数据融合、角色知识关联以及伦理安全问题等方面。本文提出了一种面向元宇宙服务生态中基于LLM的智能体的可解释情感对齐框架，旨在将事实性因素融入基于LLM的智能体的决策循环中，系统论证如何为这类智能体实现更具关联性的事实对齐。最后，本文在“线下到线下”外卖配送场景中开展了仿真实验以评估该框架的有效性，实验得到了更贴近现实的社会涌现结果。
英文摘要：
Metaverse service is a product of the convergence between Metaverse and service systems, designed to address service-related challenges concerning digital avatars, digital twins, and digital natives within Metaverse. With the rise of large language models (LLMs), agents now play a pivotal role in Metaverse service ecosystem, serving dual functions: as digital avatars representing users in the virtual realm and as service assistants (or NPCs) providing personalized support. However, during the modeling of Metaverse service ecosystems, existing LLM-based agents face significant challenges in bridging virtual-world services with real-world services, particularly regarding issues such as character data fusion, character knowledge association, and ethical safety concerns. This paper proposes an explainable emotion alignment framework for LLM-based agents in Metaverse Service Ecosystem. It aims to integrate factual factors into the decision-making loop of LLM-based agents, systematically demonstrating how to achieve more relational fact alignment for these agents. Finally, a simulation experiment in the Offline-to-Offline food delivery scenario is conducted to evaluate the effectiveness of this framework, obtaining more realistic social emergence.
