Social Simulations: from Agent-Based Modeling to Digital Twins
arXiv:2607.13693
The chapter reviews the progression of social simulation from classical agent‑based models with explicit behavioral rules, through AI‑enhanced simulations using large language models, to high‑fidelity social digital twins that replicate real socio‑technical systems.
Abstract
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.
Entry for Encyclopedia of Social Network Analysis and Mining