从规则模型到数字孪生，构建更真实的社交系统仿真。
Social Simulations: from Agent-Based Modeling to Digital Twins
- 用大语言模型增强代理行为，实现动态社会互动
- 数字孪生融合真实数据，高保真还原社会系统
- 适合研究社会机制与真实系统演化的学者
本文回顾社会模拟的演进历程，从经典的基于代理的模型（Agent-Based Models），即代理按显式规则交互，发展到依托大型语言模型（LLMs）的智能增强仿真，最终迈向社会数字孪生（Social Digital Twins）：基于真实数据、高保真度的现实社会技术系统计算表征。文章探讨各范式的理论基础、应用、优势与局限，凸显从抽象机制研究向具体社会系统真实再现的渐进转变。
原文摘要 · Abstract (English)
This book chapter covers the evolution of social simulation from classical agent-based models, in which agents interact according to explicitly defined behavioral rules, to AI-enhanced simulations based on Large Language Models and, ultimately, Social Digital Twins: high-fidelity, data-driven representations of real-world socio-technical systems. Along this trajectory, we discuss the main methodological foundations, applications, advantages, and limitations of each paradigm, highlighting the progressive shift from abstract models designed to investigate general social mechanisms toward increasingly realistic computational representations of specific social systems.
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