IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2003-26-1.html
   My bibliography  Save this article

Model-To-Model Analysis

Author

Abstract

In recent years there has been an explosion of published literature utilising Multi-Agent-Based Simulation (MABS) to study social, biological and artificial systems. This kind of work is evidenced within JASSS but is increasingly becoming part of mainstream practice across many disciplines. However, despite this plethora of interesting models, they are rarely compared, built-on or transferred between researchers. It would seem there is a dearth of "model-to-model" analysis. Rather researchers tend to work in isolation, designing all their models from scratch and reporting their results without anyone else reproducing what they found. Although the opposite extreme, where all that seems to happen is the next twist on an existing model, is not to be wished for, there are considerable dangers if everybody only works on their own model. Part of the reason for this is that models tend to be very seductive – especially to the person who has built the model. What is needed is a third person to check the results. However it is not always clear how people who are not the modeller can interpret or utilise such results, because it is very difficult to replicate simulation models from what is reported in papers. It was for these reasons that we called on the MABS community to submit papers for a model-to-model (M2M) workshop. The aim of the workshop was to gather researchers in MABS who were interested in understanding and furthering the transferability of knowledge between models. We received fourteen submissions from which (after a process of peer review) eight were presented at the workshop. Of the six articles that comprise this special issue, five were presented at the workshop.

Suggested Citation

  • David Hales & Juliette Rouchier & Bruce Edmonds, 2003. "Model-To-Model Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(4), pages 1-5.
  • Handle: RePEc:jas:jasssj:2003-26-1
    as

    Download full text from publisher

    File URL: http://jasss.soc.surrey.ac.uk/6/4/5.html
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Pierre Livet & Jean-Pierre Muller & Denis Phan & Lena Sanders, 2010. "Ontology, a Mediator for Agent-Based Modeling in Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-3.
    2. Uri Wilensky & William Rand, 2007. "Making Models Match: Replicating an Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-2.
    3. Gianluca Manzo & Delia Baldassarri, 2015. "Heuristics, Interactions, and Status Hierarchies," Sociological Methods & Research, , vol. 44(2), pages 329-387, May.
    4. Keiki Takadama & Tetsuro Kawai & Yuhsuke Koyama, 2008. "Micro- and Macro-Level Validation in Agent-Based Simulation: Reproduction of Human-Like Behaviors and Thinking in a Sequential Bargaining Game," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-9.
    5. Denis Phan & Franck Varenne, 2010. "Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-5.
    6. İlker Yıldırım & Pınar Yolum, 2009. "Hybrid models for achieving and maintaining cooperative symbiotic groups," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 8(2), pages 243-258, December.
    7. Günter Küppers & Johannes Lenhard, 2005. "Validation of Simulation: Patterns in the Social and Natural Sciences," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-3.
    8. Claudio Cioffi-Revilla, 2010. "A Methodology for Complex Social Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-7.
    9. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    10. James D. A. Millington & John Wainwright, 2016. "Comparative Approaches for Innovation in Agent-Based Modelling of Landscape Change," Land, MDPI, vol. 5(2), pages 1-4, May.
    11. J. Gareth Polhill, 2010. "ODD Updated," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 1-9.
    12. Juliette Rouchier & Claudio Cioffi-Revilla & J. Gareth Polhill & Keiki Takadama, 2008. "Progress in Model-To-Model Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-8.
    13. Bàrbara Llacay & Gilbert Peffer, 2018. "Using realistic trading strategies in an agent-based stock market model," Computational and Mathematical Organization Theory, Springer, vol. 24(3), pages 308-350, September.
    14. Klaus Wersching, 2010. "Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover," Post-Print hal-00849408, HAL.
    15. Wolfgang Radax & Bernhard Rengs, 2010. "Prospects and Pitfalls of Statistical Testing: Insights from Replicating the Demographic Prisoner's Dilemma," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 1-1.
    16. Wersching, Klaus, 2010. "Schumpeterian competition, technological regimes and learning through knowledge spillover," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 482-493, September.
    17. Xavier Vilà, 2008. "A Model-To-Model Analysis of Bertrand Competition," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-11.
    18. Martin Neumann, 2007. "Complexity of social stability: a model-to-model analysis of Yugoslavia's decline," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 5(2), pages 92-111.
    19. Georg Holtz & Christian Schnülle & Malcolm Yadack & Jonas Friege & Thorben Jensen & Pablo Thier & Peter Viebahn & Émile J. L. Chappin, 2020. "Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies," Energies, MDPI, vol. 13(22), pages 1-26, November.

    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:2003-26-1. 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.