IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v118y2013icp8-17.html
   My bibliography  Save this article

Global sensitivity/uncertainty analysis for agent-based models

Author

Listed:
  • Fonoberova, Maria
  • Fonoberov, Vladimir A.
  • Mezić, Igor

Abstract

Agent-based models simulate simultaneous actions and interactions of multiple agents, in an attempt to re-create and predict the appearance of complex phenomena. We propose to use global sensitivity analysis as a tool for analyzing and evaluating agent-based models. A general approach for applying the global sensitivity analysis to agent-based models is presented and tested on the example of a socio-cultural agent-based model we developed earlier [45]. We identify the most significant parameters in the model and uncover their contributions to the outputs of interest. Methodology of model reduction for agent-based models is discussed and demonstrated for the aforementioned model.

Suggested Citation

  • Fonoberova, Maria & Fonoberov, Vladimir A. & Mezić, Igor, 2013. "Global sensitivity/uncertainty analysis for agent-based models," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 8-17.
  • Handle: RePEc:eee:reensy:v:118:y:2013:i:c:p:8-17
    DOI: 10.1016/j.ress.2013.04.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832013000999
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2013.04.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. Saltelli, Andrea & Ratto, Marco & Tarantola, Stefano & Campolongo, Francesca, 2006. "Sensitivity analysis practices: Strategies for model-based inference," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1109-1125.
    3. Maria Fonoberova & Vladimir A. Fonoberov & Igor Mezic & Jadranka Mezic & P. Jeffrey Brantingham, 2012. "Nonlinear Dynamics of Crime and Violence in Urban Settings," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-2.
    4. Happe, Kathrin, 2005. "Agent-Based Modelling and Sensitivity Analysis by Experimental Design and Metamodelling: An Application to Modelling Regional Structural Change," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24464, European Association of Agricultural Economists.
    5. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    6. Kaegi, M. & Mock, R. & Kröger, W., 2009. "Analyzing maintenance strategies by agent-based simulations: A feasibility study," Reliability Engineering and System Safety, Elsevier, vol. 94(9), pages 1416-1421.
    7. Trucano, T.G. & Swiler, L.P. & Igusa, T. & Oberkampf, W.L. & Pilch, M., 2006. "Calibration, validation, and sensitivity analysis: What's what," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1331-1357.
    8. Sobol’, I.M. & Kucherenko, S., 2009. "Derivative based global sensitivity measures and their link with global sensitivity indices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(10), pages 3009-3017.
    9. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Chenlu Ouyang & Huiqi Jiang & Qing Sheng & Guannan Liu & Minghui Jiang, 2022. "Tripartite Evolutionary Game Analysis for Plastic Pollution Prevention and Control under the Background of China’s Plastic Ban," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    2. Arika Ligmann-Zielinska & Daniel B Kramer & Kendra Spence Cheruvelil & Patricia A Soranno, 2014. "Using Uncertainty and Sensitivity Analyses in Socioecological Agent-Based Models to Improve Their Analytical Performance and Policy Relevance," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-13, October.
    3. Priscilla Avegliano & Jaime Simão Sichman, 2023. "Equation-Based Versus Agent-Based Models: Why Not Embrace Both for an Efficient Parameter Calibration?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(4), pages 1-3.
    4. Lee, Ju-Sung & Filatova, Tatiana & Ligmann-Zielinska, Arika & Hassani-Mahmooei, Behrooz & Stonedahl, Forrest & Lorscheid, Iris & Voinov, Alexey & Polhill, J. Gareth & Sun, Zhanli & Parker, Dawn C., 2015. "The complexities of agent-based modeling output analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 18(4).

    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. Pannier, S. & Graf, W., 2015. "Sectional global sensitivity measures," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 110-117.
    2. Drignei, Dorin, 2011. "A general statistical model for computer experiments with time series output," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 460-467.
    3. James Hogg & Maria Fonoberova & Igor Mezić & Ryan Mohr, 2019. "Koopman Mode Analysis of agent-based models of logistics processes," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-37, September.
    4. Narkuniene, Asta & Poskas, Povilas & Kilda, Raimondas & Bartkus, Gytis, 2015. "Uncertainty and sensitivity analysis of radionuclide migration through the engineered barriers of deep geological repository: Case of RBMK-1500 SNF," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 8-16.
    5. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046, September.
    6. Yu, W. & Harris, T.J., 2009. "Parameter uncertainty effects on variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 596-603.
    7. Helton, Jon C. & Pilch, Martin & Sallaberry, Cédric J., 2014. "Probability of loss of assured safety in systems with multiple time-dependent failure modes: Representations with aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 171-200.
    8. Helton, J.C. & Johnson, J.D. & Oberkampf, W.L., 2007. "Verification of the calculation of probability of loss of assured safety in temperature-dependent systems with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1363-1373.
    9. Pilch, Martin & Trucano, Timothy G. & Helton, Jon C., 2011. "Ideas underlying the Quantification of Margins and Uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 965-975.
    10. William Rand & Christian Stummer, 2021. "Agent‐based modeling of new product market diffusion: an overview of strengths and criticisms," Annals of Operations Research, Springer, vol. 305(1), pages 425-447, October.
    11. Cao, Jiaokun & Du, Farong & Ding, Shuiting, 2013. "Global sensitivity analysis for dynamic systems with stochastic input processes," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 106-117.
    12. Xiang Peng & Xiaoqing Xu & Jiquan Li & Shaofei Jiang, 2021. "A Sampling-Based Sensitivity Analysis Method Considering the Uncertainties of Input Variables and Their Distribution Parameters," Mathematics, MDPI, vol. 9(10), pages 1-18, May.
    13. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    14. Zentner, Irmela & Tarantola, Stefano & de Rocquigny, E., 2011. "Sensitivity analysis for reliable design verification of nuclear turbosets," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 391-397.
    15. Ignacio Ormazábal & F. A. Borotto & H. F. Astudillo, 2017. "Influence of Money Distribution on Civil Violence Model," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    16. Helton, Jon C., 2011. "Quantification of margins and uncertainties: Conceptual and computational basis," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 976-1013.
    17. Helton, J.C. & Johnson, J.D. & Oberkampf, W.L., 2007. "Verification test problems for the calculation of probability of loss of assured safety in temperature-dependent systems with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1374-1387.
    18. Helton, Jon C. & Sallaberry, Cedric J., 2009. "Computational implementation of sampling-based approaches to the calculation of expected dose in performance assessments for the proposed high-level radioactive waste repository at Yucca Mountain, Nev," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 699-721.
    19. Maksudul Alam & Xinwei Deng & Casandra Philipson & Josep Bassaganya-Riera & Keith Bisset & Adria Carbo & Stephen Eubank & Raquel Hontecillas & Stefan Hoops & Yongguo Mei & Vida Abedi & Madhav Marathe, 2015. "Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-25, September.
    20. Imron, Muhammad Ali & Gergs, Andre & Berger, Uta, 2012. "Structure and sensitivity analysis of individual-based predator–prey models," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 71-81.

    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:eee:reensy:v:118:y:2013:i:c:p:8-17. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.