Ghaffarzadegan, NavidMajumdar, AritraWilliams, RossHosseinichimeh, Niyousha2024-01-252024-01-252024-01Ghaffarzadegan, N., Majumdar, A., Williams, R., & Hosseinichimeh, N. (2024). Generative agent‐based modeling: an introduction and tutorial. System Dynamics Review. https://doi.org/10.1002/sdr.1761https://hdl.handle.net/10919/117686We discuss the emerging new opportunity for building feedback-rich computational models of social systems using generative artificial intelligence. Referred to as Generative Agent-Based Models (GABMs), such individual-level models utilize large language models to represent human decision-making in social settings. We provide a GABM case in which human behavior can be incorporated in simulation models by coupling a mechanistic model of human interactions with a pre-trained large language model. This is achieved by introducing a simple GABM of social norm diffusion in an organization. For educational purposes, the model is intentionally kept simple. We examine a wide range of scenarios and the sensitivity of the results to several changes in the prompt. We hope the article and the model serve as a guide for building useful dynamic models of various social systems that include realistic human reasoning and decision-making.application/pdfenIn CopyrightGenerative agentgenerative artificial intelligenceagent-based modelgenerative agent-based modelsystem dynamicsChatGPTArticle - Refereedhttps://doi.org/10.1002/sdr.1761abs/2309.11456Ghaffarzadegan, Navid [0000-0003-3632-8588]