IDEAS home Printed from https://ideas.repec.org/p/isu/genstf/202001010800001690.html

Methodological Issues of Spatial Agent-Based Models

Author

Listed:
  • Manson, Steven
  • An, Li
  • Clarke, Keith C.
  • Heppenstall, Alison
  • Koch, Jennifer
  • Krzyzanowski, Brittany
  • Morgan, Fraser
  • O'Sullivan, David
  • Runck, Bryan C.
  • Shook, Eric
  • Tesfatsion, Leigh

Abstract

Agent based modeling (ABM) is a standard tool that is useful across many disciplines. Despite widespread and mounting interest in ABM, even broader adoption has been hindered by a set of methodological challenges that run from issues around basic tools to the need for a more complete conceptual foundation for the approach. After several decades of progress, ABMs remain difficult to develop and use for many students, scholars, and policy makers. This difficulty holds especially true for models designed to represent spatial patterns and processes across a broad range of human, natural, and human-environment systems. In this paper, we describe the methodological challenges facing further development and use of spatial ABM (SABM) and suggest some potential solutions from multiple disciplines. We first define SABM to narrow our object of inquiry, and then explore how spatiality is a source of both advantages and challenges. We examine how time interacts with space in models and delve into issues of model development in general and modeling frameworks and tools specifically. We draw on lessons and insights from fields with a history of ABM contributions, including economics, ecology, geography, ecology, anthropology, and spatial science with the goal of identifying promising ways forward for this powerful means of modeling.

Suggested Citation

  • Manson, Steven & An, Li & Clarke, Keith C. & Heppenstall, Alison & Koch, Jennifer & Krzyzanowski, Brittany & Morgan, Fraser & O'Sullivan, David & Runck, Bryan C. & Shook, Eric & Tesfatsion, Leigh, 2020. "Methodological Issues of Spatial Agent-Based Models," ISU General Staff Papers 202001010800001690, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genstf:202001010800001690
    as

    Download full text from publisher

    File URL: https://dr.lib.iastate.edu/server/api/core/bitstreams/1576d467-61f2-4907-bd2a-3227d5621d60/content
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lea Kaftan, 2024. "Party Competition Over Democracy: Democracy as Electoral Issue in Germany," Politics and Governance, Cogitatio Press, vol. 12.
    2. Eichfelder, Sebastian & Kluska, Mike & Knaisch, Jonas & Selle, Juliane, 2021. "Senkung der Unternehmenssteuerlast versus Förderung von Investitionen: Was ist die bessere Strategie zur Förderung der Standortattraktivität Deutschlands?," arqus Discussion Papers in Quantitative Tax Research 263, arqus - Arbeitskreis Quantitative Steuerlehre.
    3. John C. Stevenson, 2021. "Population and Inequality Dynamics in Simple Economies," Papers 2101.09817, arXiv.org, revised Aug 2021.
    4. Eichfelder, Sebastian & Kluska, Mike & Knaisch, Jonas & Selle, Juliane, 2021. "Senkung der Unternehmenssteuerlast versus Förderung von Investitionen: Was ist die bessere Strategie zur Förderung der Standortattraktivität Deutschlands?," arqus Discussion Papers in Quantitative Tax Research 266, arqus - Arbeitskreis Quantitative Steuerlehre.
    5. Salihoğlu, Tayfun & Albayrak, Ayşe Nur & Eryılmaz, Yaşasın, 2021. "A method for the determination of urban transformation areas in Kocaeli," Land Use Policy, Elsevier, vol. 109(C).
    6. Li An & Volker Grimm & Billie L. Turner II, 2020. "Editorial: Meeting Grand Challenges in Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(1), pages 1-13.
    7. An, Li & Grimm, Volker & Sullivan, Abigail & Turner II, B.L. & Malleson, Nicolas & Heppenstall, Alison & Vincenot, Christian & Robinson, Derek & Ye, Xinyue & Liu, Jianguo & Lindkvist, Emilie & Tang, W, 2021. "Challenges, tasks, and opportunities in modeling agent-based complex systems," Ecological Modelling, Elsevier, vol. 457(C).
    8. Zamponi, Virginia & O’Brien, Kevin & Jensen, Erik & Feldhaus, Brandon & Moore, Russell & Lynch, Christopher J. & Gore, Ross, 2023. "Understanding and assessing demographic (in)equity resulting from extreme heat and direct sunlight exposure due to lack of tree canopies in Norfolk, VA using agent-based modeling," Ecological Modelling, Elsevier, vol. 483(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:isu:genstf:202001010800001690. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Curtis Balmer (email available below). General contact details of provider: https://edirc.repec.org/data/deiasus.html .

    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.