IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2013-71-3.html
   My bibliography  Save this article

How Do Agents Make Decisions? A Survey

Author

Abstract

When designing an agent-based simulation, an important question to answer is how to model the decision making processes of the agents in the system. A large number of agent decision making models can be found in the literature, each inspired by different aims and research questions. In this paper we provide a review of 14 agent decision making architectures that have attracted interest. They range from production-rule systems to psychologically- and neurologically-inspired approaches. For each of the architectures we give an overview of its design, highlight research questions that have been answered with its help and outline the reasons for the choice of the decision making model provided by the originators. Our goal is to provide guidelines about what kind of agent decision making model, with which level of simplicity or complexity, to use for which kind of research question.

Suggested Citation

  • Tina Balke & Nigel Gilbert, 2014. "How Do Agents Make Decisions? A Survey," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(4), pages 1-13.
    • Handle: RePEc:jas:jasssj:2013-71-3
    as

    Download full text from publisher

    File URL: https://www.jasss.org/17/4/13/13.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Petra Ahrweiler, 2017. "Agent-based simulation for science, technology, and innovation policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 391-415, January.
    2. Cristiano CODAGNONE & Giovanni LIVA & Egidijus BARCEVICIUS & Gianluca MISURACA & Luka KLIMAVICIUTE & Michele BENEDETTI & Irene VANINI & Giancarlo VECCHI & Emily RYEN GLOINSON & Katherine STEWART & Sti, 2020. "Assessing the impacts of digital government transformation in the EU: Conceptual framework and empirical case studies," JRC Research Reports JRC120865, Joint Research Centre.
    3. Lorraine Dodd, 2019. "Choice-making and choose-ables: making decision agents more human and choosy," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 7(1), pages 101-115, May.
    4. David Anzola & Peter Barbrook-Johnson & Juan I. Cano, 2017. "Self-organization and social science," Computational and Mathematical Organization Theory, Springer, vol. 23(2), pages 221-257, June.
    5. repec:eur:ejfejr:7 is not listed on IDEAS
    6. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.
    7. Ida Nadia S. Djenontin & Leo C. Zulu & Arika Ligmann-Zielinska, 2020. "Improving Representation of Decision Rules in LUCC-ABM: An Example with an Elicitation of Farmers’ Decision Making for Landscape Restoration in Central Malawi," Sustainability, MDPI, vol. 12(13), pages 1-35, July.
    8. Pablo Pico-Valencia & Juan A Holgado-Terriza, 2018. "Agentification of the Internet of Things: A systematic literature review," International Journal of Distributed Sensor Networks, , vol. 14(10), pages 15501477188, October.
    9. Gianluca Misuraca & Luigi Geppert & Cristiano Codagnone, 2017. "i-FRAME – Assessing impacts of social policy innovation in the EU: Proposed methodological framework to evaluate socio-economic returns on investment of social policy innovations," JRC Research Reports JRC108078, Joint Research Centre.
    10. María Elena Orduña Alegría & Niels Schütze & Samuel C. Zipper, 2020. "A Serious Board Game to Analyze Socio-Ecological Dynamics towards Collaboration in Agriculture," Sustainability, MDPI, vol. 12(13), pages 1-19, June.
    11. Juana Castro & Stefan Drews & Filippos Exadaktylos & Joël Foramitti & Franziska Klein & Théo Konc & Ivan Savin & Jeroen van den Bergh, 2020. "A review of agent‐based modeling of climate‐energy policy," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(4), July.
    12. Amir Ali Safaei Pirooz & Mohammad J. Sanjari & Young-Jin Kim & Stuart Moore & Richard Turner & Wayne W. Weaver & Dipti Srinivasan & Josep M. Guerrero & Mohammad Shahidehpour, 2023. "Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation," Energies, MDPI, vol. 16(8), pages 1-16, April.
    13. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    14. Noeldeke, Beatrice & Winter, Etti & Ntawuhiganayo, Elisée Bahati, 2022. "Representing human decision-making in agent-based simulation models: Agroforestry adoption in rural Rwanda," Ecological Economics, Elsevier, vol. 200(C).
    15. Anna Borawska & Malgorzata Latuszynska, 2020. "Incorporating Neuroscience Data into Agent-Based Simulation Models of Buyer Behavior," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1197-1212.
    16. Hazel Squires & Michael P. Kelly & Nigel Gilbert & Falko Sniehotta & Robin C. Purshouse, 2023. "The long‐term effectiveness and cost‐effectiveness of public health interventions; how can we model behavior? A review," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2836-2854, December.
    17. Schlüter, Maja & Baeza, Andres & Dressler, Gunnar & Frank, Karin & Groeneveld, Jürgen & Jager, Wander & Janssen, Marco A. & McAllister, Ryan R.J. & Müller, Birgit & Orach, Kirill & Schwarz, Nina & Wij, 2017. "A framework for mapping and comparing behavioural theories in models of social-ecological systems," Ecological Economics, Elsevier, vol. 131(C), pages 21-35.

    More about this item

    Keywords

    Decision Making; Agents; Survey;
    All these keywords.

    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:jas:jasssj:2013-71-3. 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: Francesco Renzini (email available below). General contact details of provider: .

    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.