IDEAS home Printed from https://ideas.repec.org/a/bla/sysdyn/v40y2024i1ne1761.html
   My bibliography  Save this article

Generative agent‐based modeling: an introduction and tutorial

Author

Listed:
  • Navid Ghaffarzadegan
  • Aritra Majumdar
  • Ross Williams
  • Niyousha Hosseinichimeh

Abstract

We 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 into 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. © 2024 System Dynamics Society.

Suggested Citation

  • Navid Ghaffarzadegan & Aritra Majumdar & Ross Williams & Niyousha Hosseinichimeh, 2024. "Generative agent‐based modeling: an introduction and tutorial," System Dynamics Review, System Dynamics Society, vol. 40(1), January.
    • Handle: RePEc:bla:sysdyn:v:40:y:2024:i:1:n:e1761
    DOI: 10.1002/sdr.1761
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/sdr.1761
    Download Restriction: no
    File URL: https://libkey.io/10.1002/sdr.1761?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vince Barabba & Chet Huber & Fred Cooke & Nick Pudar & Jim Smith & Mark Paich, 2002. "A Multimethod Approach for Creating New Business Models: The General Motors OnStar Project," Interfaces, INFORMS, vol. 32(1), pages 20-34, February.
    2. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," NBER Working Papers 31122, National Bureau of Economic Research, Inc.
    3. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    4. Erling Moxnes, 2023. "Challenges for sustainability: misperceptions and misleading advice," System Dynamics Review, System Dynamics Society, vol. 39(3), pages 185-206, July.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    7. Navid Ghaffarzadegan & Richard C. Larson, 2018. "SD meets OR: a new synergy to address policy problems," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 327-353, January.
    8. Neil Ferguson, 2007. "Capturing human behaviour," Nature, Nature, vol. 446(7137), pages 733-733, April.
    9. C. J. Ancker & A. V. Gafarian, 1963. "Some Queuing Problems with Balking and Reneging. I," Operations Research, INFORMS, vol. 11(1), pages 88-100, February.
    10. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    11. John Sterman, 2018. "System dynamics at sixty: the path forward," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 5-47, January.
    12. Philipp Wunderlich & Andreas Größler & Nicole Zimmermann & Jac A. M. Vennix, 2014. "Managerial influence on the diffusion of innovations within intra-organizational networks," System Dynamics Review, System Dynamics Society, vol. 30(3), pages 161-185, July.
    13. C. J. Ancker & A. V. Gafarian, 1963. "Some Queuing Problems with Balking and Reneging---II," Operations Research, INFORMS, vol. 11(6), pages 928-937, December.
    14. Argyle, Lisa P. & Busby, Ethan C. & Fulda, Nancy & Gubler, Joshua R. & Rytting, Christopher & Wingate, David, 2023. "Out of One, Many: Using Language Models to Simulate Human Samples," Political Analysis, Cambridge University Press, vol. 31(3), pages 337-351, July.
    15. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," Papers 2301.07543, arXiv.org.
    16. Sumaiya Haque & Hesam Mahmoudi & Navid Ghaffarzadegan & Konstantinos Triantis, 2023. "Mental models, cognitive maps, and the challenge of quantitative analysis of their network representations," System Dynamics Review, System Dynamics Society, vol. 39(2), pages 152-170, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Niyousha Hosseinichimeh & Aritra Majumdar & Ross Williams & Navid Ghaffarzadegan, 2024. "From text to map: a system dynamics bot for constructing causal loop diagrams," System Dynamics Review, System Dynamics Society, vol. 40(3), July.
    2. Jiangbo Yu, 2022. "An elementary mechanism for simultaneously modeling discrete decisions and decision times," System Dynamics Review, System Dynamics Society, vol. 38(3), pages 215-245, July.
    3. Navid Ghaffarzadegan & Richard C. Larson, 2018. "SD meets OR: a new synergy to address policy problems," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 327-353, January.
    4. Navid Ghaffarzadegan & Sarah Mostafavi & Hyunjung Kim, 2023. "Sociotechnical interdependencies and tipping‐point dynamics in data‐intensive services," System Dynamics Review, System Dynamics Society, vol. 39(1), pages 5-31, January.
    5. Jingru Jia & Zehua Yuan & Junhao Pan & Paul E. McNamara & Deming Chen, 2024. "Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context," Papers 2406.05972, arXiv.org, revised Oct 2024.
    6. Navid Ghaffarzadegan & Hazhir Rahmandad, 2020. "Simulation‐based estimation of the early spread of COVID‐19 in Iran: actual versus confirmed cases," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 101-129, January.
    7. Andrea Coletta & Kshama Dwarakanath & Penghang Liu & Svitlana Vyetrenko & Tucker Balch, 2024. "LLM-driven Imitation of Subrational Behavior : Illusion or Reality?," Papers 2402.08755, arXiv.org.
    8. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    9. Arieh Gavious & Oded Lowengart, 2012. "Price–quality relationship in the presence of asymmetric dynamic reference quality effects," Marketing Letters, Springer, vol. 23(1), pages 137-161, March.
    10. Kevin Leyton-Brown & Paul Milgrom & Neil Newman & Ilya Segal, 2024. "Artificial Intelligence and Market Design: Lessons Learned from Radio Spectrum Reallocation," NBER Chapters, in: New Directions in Market Design, National Bureau of Economic Research, Inc.
    11. Jaekwon Chung, 2020. "Effect of Quality Uncertainty, Regulatory Focus, and Promotional Strategies on Perceived Savings for Sustainable Marketing," Sustainability, MDPI, vol. 12(14), pages 1-16, July.
    12. Kirshner, Samuel N., 2024. "GPT and CLT: The impact of ChatGPT's level of abstraction on consumer recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    13. Pala, Ali & Zhuang, Jun, 2018. "Security screening queues with impatient applicants: A new model with a case study," European Journal of Operational Research, Elsevier, vol. 265(3), pages 919-930.
    14. Claire F. Brereton & Paul Jagals, 2021. "Applications of Systems Science to Understand and Manage Multiple Influences within Children’s Environmental Health in Least Developed Countries: A Causal Loop Diagram Approach," IJERPH, MDPI, vol. 18(6), pages 1-23, March.
    15. Zengqing Wu & Run Peng & Xu Han & Shuyuan Zheng & Yixin Zhang & Chuan Xiao, 2023. "Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations," Papers 2311.06330, arXiv.org, revised Dec 2023.
    16. Amina Angelika Bouchentouf & Aicha Messabihi, 2018. "Heterogeneous two-server queueing system with reverse balking and reneging," OPSEARCH, Springer;Operational Research Society of India, vol. 55(2), pages 251-267, June.
    17. Veeraruna Kavitha & Jayakrishnan Nair & Raman Kumar Sinha, 2019. "Pseudo conservation for partially fluid, partially lossy queueing systems," Annals of Operations Research, Springer, vol. 277(2), pages 255-292, June.
    18. Joshua C. Yang & Damian Dailisan & Marcin Korecki & Carina I. Hausladen & Dirk Helbing, 2024. "LLM Voting: Human Choices and AI Collective Decision Making," Papers 2402.01766, arXiv.org, revised Aug 2024.
    19. Nir Chemaya & Daniel Martin, 2023. "Perceptions and Detection of AI Use in Manuscript Preparation for Academic Journals," Papers 2311.14720, arXiv.org, revised Jan 2024.
    20. Lijia Ma & Xingchen Xu & Yong Tan, 2024. "Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines," Papers 2402.19421, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:sysdyn:v:40:y:2024:i:1:n:e1761. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/0883-7066 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.