IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v4y2015i2p281-299d48178.html
   My bibliography  Save this article

Agent-Based Models as “Interested Amateurs”

Author

Listed:
  • Peter George Johnson

    (Centre for Research in Social Simulation, University of Surrey, Guildford GU2 7XH, UK)

Abstract

This paper proposes the use of agent-based models (ABMs) as “interested amateurs” in policy making, and uses the example of the SWAP model of soil and water conservation adoption to demonstrate the potential of this approach. Daniel Dennett suggests experts often talk past or misunderstand each other, seek to avoid offending each other or appearing ill-informed and generally err on the side of under-explaining a topic. Dennett suggests that these issues can be overcome by including “interested amateurs” in discussions between experts. In the context of land use policy debates, and policy making more generally, this paper suggests that ABMs have particular characteristics that make them excellent potential “interested amateurs” in discussions between our experts: policy stakeholders. This is demonstrated using the SWAP (Soil and Water Conservation Adoption) model, which was used with policy stakeholders in Ethiopia. The model was successful in focussing discussion, inviting criticism, dealing with sensitive topics and drawing out understanding between stakeholders. However, policy stakeholders were still hesitant about using such a tool. This paper reflects on these findings and attempts to plot a way forward for the use of ABMs as “interested amateurs” and, in the process, make clear the differences in approach to other participatory modelling efforts.

Suggested Citation

  • Peter George Johnson, 2015. "Agent-Based Models as “Interested Amateurs”," Land, MDPI, vol. 4(2), pages 1-19, April.
  • Handle: RePEc:gam:jlands:v:4:y:2015:i:2:p:281-299:d:48178
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/4/2/281/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/4/2/281/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Olivier Barreteau, 2003. "Our Companion Modelling Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(2), pages 1-1.
    2. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    3. Jager, W. & Janssen, M. A. & De Vries, H. J. M. & De Greef, J. & Vlek, C. A. J., 2000. "Behaviour in commons dilemmas: Homo economicus and Homo psychologicus in an ecological-economic model," Ecological Economics, Elsevier, vol. 35(3), pages 357-379, December.
    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. George Van Voorn & Geerten Hengeveld & Jan Verhagen, 2020. "An agent based model representation to assess resilience and efficiency of food supply chains," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-27, November.
    2. Bert, Federico E. & Rovere, Santiago L. & Macal, Charles M. & North, Michael J. & Podestá, Guillermo P., 2014. "Lessons from a comprehensive validation of an agent based-model: The experience of the Pampas Model of Argentinean agricultural systems," Ecological Modelling, Elsevier, vol. 273(C), pages 284-298.
    3. Chion, Clément & Lamontagne, P. & Turgeon, S. & Parrott, L. & Landry, J.-A. & Marceau, D.J. & Martins, C.C.A. & Michaud, R. & Ménard, N. & Cantin, G. & Dionne, S., 2011. "Eliciting cognitive processes underlying patterns of human–wildlife interactions for agent-based modelling," Ecological Modelling, Elsevier, vol. 222(14), pages 2213-2226.
    4. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.
    5. 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.
    6. Barnaud, Cécile & Bousquet, François & Trebuil, Guy, 2008. "Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand," Ecological Economics, Elsevier, vol. 66(4), pages 615-627, July.
    7. Bourceret, Amélie & Amblard, Laurence & Mathias, Jean-Denis, 2022. "Adapting the governance of social–ecological systems to behavioural dynamics: An agent-based model for water quality management using the theory of planned behaviour," Ecological Economics, Elsevier, vol. 194(C).
    8. Gawith, David & Hodge, Ian & Morgan, Fraser & Daigneault, Adam, 2020. "Climate change costs more than we think because people adapt less than we assume," Ecological Economics, Elsevier, vol. 173(C).
    9. Apetrei, Cristina I. & Strelkovskii, Nikita & Khabarov, Nikolay & Javalera Rincón, Valeria, 2024. "Improving the representation of smallholder farmers’ adaptive behaviour in agent-based models: Learning-by-doing and social learning," Ecological Modelling, Elsevier, vol. 489(C).
    10. Geovanna Hinojoza-Castro & Montserrat Gómez-Delgado & Wenseslao Plata-Rocha, 2022. "Real Estate Developers as Agents in the Simulation of Urban Sprawl," Sustainability, MDPI, vol. 14(15), pages 1-12, July.
    11. Dinar, Ariel & Farolfi, Stefano & Patrone, Fioravante & Rowntree, Kate, 2006. "TO NEGOTIATE OR TO GAME THEORIZE: Negotiation vs. Game Theory Outcomes for Water Allocation Problems in the Kat Basin, South Africa," Working Papers 60888, University of Pretoria, Department of Agricultural Economics, Extension and Rural Development.
    12. Tardy, Olivia & Lenglos, Christophe & Lai, Sandra & Berteaux, Dominique & Leighton, Patrick A., 2023. "Rabies transmission in the Arctic: An agent-based model reveals the effects of broad-scale movement strategies on contact risk between Arctic foxes," Ecological Modelling, Elsevier, vol. 476(C).
    13. Vimercati, Giovanni & Hui, Cang & Davies, Sarah J. & Measey, G. John, 2017. "Integrating age structured and landscape resistance models to disentangle invasion dynamics of a pond-breeding anuran," Ecological Modelling, Elsevier, vol. 356(C), pages 104-116.
    14. Jagadish, Arundhati & Dwivedi, Puneet & McEntire, Kira D. & Chandar, Mamta, 2019. "Agent-based modeling of “cleaner” cookstove adoption and woodfuel use: An integrative empirical approach," Forest Policy and Economics, Elsevier, vol. 106(C), pages 1-1.
    15. Hinker, Jonas & Hemkendreis, Christian & Drewing, Emily & März, Steven & Hidalgo Rodríguez, Diego I. & Myrzik, Johanna M.A., 2017. "A novel conceptual model facilitating the derivation of agent-based models for analyzing socio-technical optimality gaps in the energy domain," Energy, Elsevier, vol. 137(C), pages 1219-1230.
    16. Tianran Ding & Wouter Achten, 2023. "Coupling agent-based modeling with territorial LCA to support agricultural land-use planning," ULB Institutional Repository 2013/359527, ULB -- Universite Libre de Bruxelles.
    17. Jascha-Alexander Koch & Jens Lausen & Moritz Kohlhase, 2021. "Internalizing the externalities of overfunding: an agent-based model approach for analyzing the market dynamics on crowdfunding platforms," Journal of Business Economics, Springer, vol. 91(9), pages 1387-1430, November.
    18. Crevier, Lucas Phillip & Salkeld, Joseph H & Marley, Jessa & Parrott, Lael, 2021. "Making the best possible choice: Using agent-based modelling to inform wildlife management in small communities," Ecological Modelling, Elsevier, vol. 446(C).
    19. Ulfia A. Lenfers & Julius Weyl & Thomas Clemen, 2018. "Firewood Collection in South Africa: Adaptive Behavior in Social-Ecological Models," Land, MDPI, vol. 7(3), pages 1-17, August.
    20. David, Viviane & Joachim, Sandrine & Tebby, Cleo & Porcher, Jean-Marc & Beaudouin, Rémy, 2019. "Modelling population dynamics in mesocosms using an individual-based model coupled to a bioenergetics model," Ecological Modelling, Elsevier, vol. 398(C), pages 55-66.

    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:gam:jlands:v:4:y:2015:i:2:p:281-299:d:48178. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.