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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. 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).
    3. 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.
    4. 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).

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