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Verifying agent-based models with steady-state analysis

Author

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  • James E. Gentile

    (University of Notre Dame)

  • Gregory J. Davis

    (University of Notre Dame)

  • Samuel S. C. Rund

    (University of Notre Dame)

Abstract

Agent-based modeling has been well received in the simulation community. Complex systems are simulated by many autonomous agents whose behavior is defined by a conceptual model. However, the model can be improperly implemented or misinterpreted resulting in an implementation that does not reflect the conceptual rules. It is imperative that the implementation’s function be tested against the model’s expected outcome. In this paper, we present certain steady-state techniques that can be used to verify the operation of agent-based simulations. These methods are introduced and then applied to an ecological model which simulates reproductive dynamics of mosquitoes.

Suggested Citation

  • James E. Gentile & Gregory J. Davis & Samuel S. C. Rund, 2012. "Verifying agent-based models with steady-state analysis," Computational and Mathematical Organization Theory, Springer, vol. 18(4), pages 404-418, December.
    • Handle: RePEc:spr:comaot:v:18:y:2012:i:4:d:10.1007_s10588-012-9128-8
    DOI: 10.1007/s10588-012-9128-8
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    References listed on IDEAS

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    1. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    2. Fatima Rateb & Bernard Pavard & Narjes Bellamine-BenSaoud & J.J. Merelo & M.G. Arenas, 2005. "Modeling Malaria with Multi-Agent Systems," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 1(2), pages 17-27, April.
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    Cited by:

    1. Jianjun Lu & Shozo Tokinaga, 2016. "Cluster fluctuation in two-dimensional lattices with local interactions," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 237-259, June.
    2. Madeira, Carlos, 2019. "Measuring the covariance risk of consumer debt portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 21-38.
    3. Bing Bai & Byungjoon Yoo & Xiuquan Deng & Iljoo Kim & Dehua Gao, 2016. "Linking routines to the evolution of IT capability on agent-based modeling and simulation: a dynamic perspective," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 184-211, June.

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