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Everything you need to know about agent-based modelling and simulation

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  • C M Macal

Abstract

This paper addresses the background and current state of the field of agent-based modelling and simulation (ABMS). It revisits the issue of ABMS represents as a new development, considering the extremes of being an overhyped fad, doomed to disappear, or a revolutionary development, shifting fundamental paradigms of how research is conducted. This paper identifies key ABMS resources, publications, and communities. It also proposes several complementary definitions for ABMS, based on practice, intended to establish a common vocabulary for understanding ABMS, which seems to be lacking. It concludes by suggesting research challenges for ABMS to advance and realize its potential in the coming years.

Suggested Citation

  • C M Macal, 2016. "Everything you need to know about agent-based modelling and simulation," Journal of Simulation, Taylor & Francis Journals, vol. 10(2), pages 144-156, May.
    • Handle: RePEc:taf:tjsmxx:v:10:y:2016:i:2:p:144-156
    DOI: 10.1057/jos.2016.7
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    Cited by:

    1. Gonzalo Bustos-Turu & Koen H. van Dam & Salvador Acha & Nilay Shah, 2023. "An Agent-Based Decision Support Framework for a Prospective Analysis of Transport and Heat Electrification in Urban Areas," Energies, MDPI, vol. 16(17), pages 1-26, August.
    2. José M. Gaspar, 2018. "Bridging the Gap between Economic Modelling and Simulation: A Simple Dynamic Aggregate Demand-Aggregate Supply Model with Matlab," Journal of Applied Mathematics, Hindawi, vol. 2018, pages 1-13, January.
    3. Michael Crilly & Georgiana Varna & Alec Coaker & Rhodri Cenek Gibbon & Joshua Jackson & Niamh Ellen McDonald & Deegan Ramsey Smith, 2026. "Experimenting With Gamification and Geogames in Urban Planning: A Systematic Literature Review," Urban Planning, Cogitatio Press, vol. 11.
    4. Alexander L Martinez & Lance E Champagne & Phillip M LaCasse, 2026. "Simulating autonomous drone behaviors in an anti-access area denial (A2AD) environment," The Journal of Defense Modeling and Simulation, , vol. 23(2), pages 325-334, April.
    5. Andrei I. Vlad & Alexei A. Romanyukha & Tatiana E. Sannikova, 2024. "Parameter Tuning of Agent-Based Models: Metaheuristic Algorithms," Mathematics, MDPI, vol. 12(14), pages 1-21, July.
    6. Ventura, Paulo C. & Tokuda, Eric K. & da F. Costa, Luciano & Rodrigues, Francisco A., 2023. "A Markov chain for metapopulations of small sizes with attraction landscape," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    7. Giacomo Ravaioli & Tiago Domingos & Ricardo F. M. Teixeira, 2023. "A Framework for Data-Driven Agent-Based Modelling of Agricultural Land Use," Land, MDPI, vol. 12(4), pages 1-17, March.
    8. Hong, L. Jeff & Nelson, Barry L., 2026. "Fifty years of stochastic simulation: Where we are and where we need to go," European Journal of Operational Research, Elsevier, vol. 330(3), pages 701-714.
    9. Diego Andrés CARREÑO DUEÑAS & Walter Lugo RUIZ CASTAÑEDA, 2025. "Sustainable Regional Development And Complex Adaptive Systems: A Methodological Proposal Through Social Network Analysis," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(2), pages 85-99, December.
    10. Lorena Reyes-Rubiano & Ingrid Y. Amaya & David Medina Mayorga & Andrés Muñoz-Villamizar & Elyn Solano-Charris, 2024. "How does technological innovation impact the service time and the attraction of new customers in the financial sector? Evidence from an emerging economy," Operations Management Research, Springer, vol. 17(2), pages 596-611, June.
    11. Geng, Xin & Hu, Shi & Wang, Xunming & Cai, Diwen & Gong, Yuan, 2023. "Adaptive change of land use to nature and society in China’s agro-pastoral ecotone," Land Use Policy, Elsevier, vol. 126(C).
    12. André Rossi Kuroswiski & Felipe Leonardo Lôbo Medeiros & Monica Maria De Marchi & Angelo Passaro, 2025. "Beyond visual range air combat simulations: validation methods and analysis using agent-based models," The Journal of Defense Modeling and Simulation, , vol. 22(4), pages 387-404, October.
    13. Ye, Xu & Wang, Yu & Shafiee, Sara, 2024. "An iterative consumer-centric and technology-driven product innovation strategy based on selective and dynamic consumer attention," Technological Forecasting and Social Change, Elsevier, vol. 208(C).

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