Generative agent-based modeling: an introduction and tutorial

Who it's for: Ideal for learners with a basic understanding of agent-based modelling or generative artificial intelligence who are looking for innovative ways to integrate the two.

Why we love it: This paper introduces Generative Agent-Based Modeling (GABM) as an innovative approach for incorporating generative artificial intelligence, particularly large language models, into the simulation of social systems. By discussing a case study on social norm diffusion within a company (workers wearing blue or green shirts), it demonstrates how GABM can dynamically simulate human decision-making processes within organizational contexts. This work not only enriches the modeling toolkit for researchers but also opens new avenues for understanding the intricate dynamics of social phenomena.

Citation: Ghaffarzadegan, N., Majumdar, A., Williams, R., & Hosseinichimeh, N. (2024). Generative agent-based modeling: An introduction and tutorial. System Dynamics Review, 40(1), e1761. https://doi.org/10.1002/sdr.1761