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Simplicity and reality in computational modeling of politics

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  • Claudio Cioffi-Revilla

    (George Mason University)

Abstract

Modeling a polity based on viable scientific concepts and theoretical understanding has been a challenge in computational social science and social simulation in general and political science in particular. This paper presents a computational model of a polity (political system) in progressive versions from simple to more realistic. The model, called SimPol to highlight the fundamental structures and processes of politics in a generic society, is developed using the combined methodologies of object-based modeling (OOM), the Unified Modeling Language (UML), and the methodology of Lakatos’ research programs. SimPol demonstrates that computational models of entire political systems are methodologically feasible and scientifically viable; they can also build on and progress beyond previous theory and research to advance our understanding of how polities operate across a variety of domains (simple vs. complex) and levels of analysis (local, national, international). Both simple and realistic models are necessary, for theoretical and empirical purposes, respectively.

Suggested Citation

  • Claudio Cioffi-Revilla, 2009. "Simplicity and reality in computational modeling of politics," Computational and Mathematical Organization Theory, Springer, vol. 15(1), pages 26-46, March.
  • Handle: RePEc:spr:comaot:v:15:y:2009:i:1:d:10.1007_s10588-008-9042-2
    DOI: 10.1007/s10588-008-9042-2
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    References listed on IDEAS

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    3. Giovanni Sartori, 1994. "Comparative Constitutional Engineering," International Economic Association Series, Palgrave Macmillan, number 978-1-349-22861-4.
    4. Herbert A. Simon, 1996. "The Sciences of the Artificial, 3rd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262691914, April.
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    Cited by:

    1. Camelia Florela Voinea & Martin Neumann & Klaus G. Troitzsch, 2023. "The State and the Citizen: Overview of a complex relationship from a paradigmatic perspective," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 1-17, April.

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