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Re-thinking simulation: a methodological approach for the application of data mining in agent-based modelling

Author

Listed:
  • Javier Arroyo

    (Universidad Complutense de Madrid)

  • Samer Hassan

    (Universidad Complutense de Madrid)

  • Celia Gutiérrez

    (Universidad Complutense de Madrid)

  • Juan Pavón

    (Universidad Complutense de Madrid)

Abstract

Agent-based models informed by empirical data are growing in popularity. Many models make extensive use of collected data for the development, initialisation or validation. In parallel, models are growing in size and complexity, generating large amounts of output data. On the other hand, Data Mining is used to extract hidden patterns from large collections of data using different techniques. This work proposes the intense use of Data Mining techniques for the improvement and development of agent-based models. It presents a methodological approach explaining why and when to use Data Mining, with a formal description of each stage of the corresponding process. This is illustrated with a case study, showing the application of the proposed approach step by step.

Suggested Citation

  • Javier Arroyo & Samer Hassan & Celia Gutiérrez & Juan Pavón, 2010. "Re-thinking simulation: a methodological approach for the application of data mining in agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 16(4), pages 416-435, December.
    • Handle: RePEc:spr:comaot:v:16:y:2010:i:4:d:10.1007_s10588-010-9078-y
    DOI: 10.1007/s10588-010-9078-y
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    References listed on IDEAS

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    Cited by:

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    2. Brandon Shapiro & Andrew Crooks, 2023. "Drone strikes and radicalization: an exploration utilizing agent-based modeling and data applied to Pakistan," Computational and Mathematical Organization Theory, Springer, vol. 29(3), pages 415-433, September.

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