Date & Time: May 13, 2024, 13:30-17:00 Venue: WWW 2024, Singapore
Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Integrating large language models into agent-based modeling and simulation presents a promising avenue for enhancing simulation capabilities. This paper surveys the landscape of utilizing large language models in agent-based modeling and simulation, examining their challenges and promising future directions. In this survey, since this is an interdisciplinary field, we first introduce the background of agent-based modeling and simulation and large language model-empowered agents. We then discuss the motivation for applying large language models to agent-based simulation and systematically analyze the challenges in environment perception, human alignment, action generation, and evaluation. Most importantly, we provide a comprehensive overview of the recent works of large language model-empowered agent-based modeling and simulation in multiple scenarios, which can be divided into four domains: cyber, physical, social, and hybrid, covering simulation of both real-world and virtual environments. Finally, since this area is new and quickly evolving, we discuss the open problems and promising future directions.
We release a survey paper about agent-based modeling and simulation with large language model-empowered agents. For more details, please refer to the arXiv paper.
Chen Gao, Research-track Assistant Professor, Tsinghua University
Fengli Xu, Tenure-track Assistant Professor, Tsinghua University
Xu Chen, Associate Professor, Renmin University of China
Xiang Wang, Professor, University of Science and Technology of China
Xiangnan He, Professor, University of Science and Technology of China
Yong Li, Tenured Associate Professor, Tsinghua University