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Intending the Unintended: The act of building agent-based models as a regular source of knowledge generation

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  • Erik Johnston

    ()
    (School of Public Affairs, Arizona State University)

  • Yushim Kim

    (School of Public Affairs, Arizona State University)

  • Mitali Ayyangar

    (School of Planning, Arizona State University)

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    Abstract

    Poverty is a complex issue that is rarely conducive to analysis in laboratory or field experiments. Effective interventions that aim to decrease or eliminate poverty require an understanding of the intricate web of associated social issues. The need for this increased comprehension necessitates the use of alternative robust means of analysis: one such being agent-based modelling. The strengths of agent-based modelling to disaggregate complex social behaviours and understand them are well known. However, while people have explored how the modelling process can prove to be fruitful, the usually unintended insight gained and the knowledge engendered during the model design process goes largely unnoticed. In this paper, we aspire to show precisely how the model building process is critical in leading to unintended knowledge generation for modellers by drawing from three US based examples where agent-based modelling was used to aid research into the effects of interventions that address poverty and human development through programs and issues facing low-income families. With these examples, we illustrate some of the means to harness new knowledge generated. In our discussion, we also highlight the advantageous nature of agent-based model design as an independent source of knowledge generation. Classification-ACM-1998: I.6.5 Model Development

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    Bibliographic Info

    Article provided by Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu in its journal Interdisciplinary Description of Complex Systems.

    Volume (Year): 5 (2007)
    Issue (Month): 2 ()
    Pages: 81-91

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    Handle: RePEc:zna:indecs:v:5:y:2007:i:2:p:81-91

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    Related research

    Keywords: methods; agent-based modelling; knowledge generation; policy informatics;

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    1. John B Van Huyck & Raymond C Battalio & Richard O Beil, 1997. "Tacit coordination games, strategic uncertainty, and coordination failure," Levine's Working Paper Archive 1225, David K. Levine.
    2. Michael Moehring & Klaus G. Troitzsch, 2001. "Lake Anderson Revisited by Agents," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(3), pages 1.
    3. Cachon, Gerard P & Camerer, Colin F, 1996. "Loss-Avoidance and Forward Induction in Experimental Coordination Games," The Quarterly Journal of Economics, MIT Press, vol. 111(1), pages 165-94, February.
    4. Oliveira, Victor & Racine, Elizabeth & Olmsted, Jennifer & Ghelfi, Linda M., 2002. "The Wic Program: Background, Trends, And Issues," Food Assistance and Nutrition Research Reports 33847, United States Department of Agriculture, Economic Research Service.
    5. Xiaoguang Gong & Renbin Xiao, 2007. "Research on Multi-Agent Simulation of Epidemic News Spread Characteristics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1.
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