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Exploratory Modeling for Policy Analysis


  • Steve Bankes

    (RAND, Santa Monica, California)


Exploratory modeling is using computational experiments to assist in reasoning about systems where there is significant uncertainty. While frequently confused with the use of models to consolidate knowledge into a package that is used to predict system behavior, exploratory modeling is a very different kind of use, requiring a different methodology for model development. This paper distinguishes these two broad classes of model use describes some of the approaches used in exploratory modeling, and suggests some technological innovations needed to facilitate it.

Suggested Citation

  • Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
  • Handle: RePEc:inm:oropre:v:41:y:1993:i:3:p:435-449

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    Cited by:

    1. Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
    2. Klaus Keller & Louise I. Miltich & Alexander Robinson & Richard S.J. Tol, 2007. "How overconfident are current projections of anthropogenic carbon dioxide emissions?," Working Papers FNU-124, Research unit Sustainability and Global Change, Hamburg University, revised Jan 2007.
    3. Jan H. Kwakkel & Erik Pruyt, 2015. "Using System Dynamics for Grand Challenges: The ESDMA Approach," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(3), pages 358-375, May.
    4. repec:eee:enepol:v:110:y:2017:i:c:p:271-287 is not listed on IDEAS
    5. John H. Miller, 1996. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Working Papers 96-03-011, Santa Fe Institute.
    6. Pauline Barrieu & Sinclair Desgagn�, 2009. "Economic policy when models disagree," GRI Working Papers 4, Grantham Research Institute on Climate Change and the Environment.
    7. repec:pal:jorsoc:v:59:y:2008:i:3:d:10.1057_palgrave.jors.2602368 is not listed on IDEAS
    8. L. Andrew Bollinger & Chris Davis & Igor Nikolić & Gerard P.J. Dijkema, 2012. "Modeling Metal Flow Systems," Journal of Industrial Ecology, Yale University, vol. 16(2), pages 176-190, April.
    9. Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad, 2004. "The agricultural policy simulator (AgriPoliS): an agent-based model to study structural change in agriculture (Version 1.0)," IAMO Discussion Papers 71, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    10. Pauline Barrieu & Bernard Sinclair-Desgagné, 2009. "Economic Policy when Models Disagree," CIRANO Working Papers 2009s-03, CIRANO.
    11. Christine Chou & Steven O. Kimbrough, 2016. "An agent-based model of organizational ambidexterity decisions and strategies in new product development," Computational and Mathematical Organization Theory, Springer, vol. 22(1), pages 4-46, March.
    12. David C. Lane & Özge Pala & Yaman Barlas & Willem L. Auping & Erik Pruyt & Jan H. Kwakkel, 2015. "Societal Ageing in the Netherlands: A Robust System Dynamics Approach," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(4), pages 485-501, July.
    13. Erik Pruyt & Willem L. Auping & Jan H. Kwakkel, 2015. "Ebola in West Africa: Model-Based Exploration of Social Psychological Effects and Interventions," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(1), pages 2-14, January.
    14. Shu-Heng Chen & Connie Houning Wang & Weikai Chen, 2017. "Matching Impacts of School Admission Mechanisms: An Agent-Based Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 217-241, March.
    15. Erik Pruyt & Tushith Islam, 2015. "On generating and exploring the behavior space of complex models," System Dynamics Review, System Dynamics Society, vol. 31(4), pages 220-249, October.
    16. repec:eee:rensus:v:82:y:2018:i:p3:p:3441-3451 is not listed on IDEAS


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