On the Quality of a Social Simulation Model: A Lifecycle Framework

  • Claudio Cioffi-Revilla
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 229)


Computational social science grows from several research traditions with roots in The Enlightenment and earlier origins in Aristotle’s comparative analysis of social systems. Extant standards of scientific quality and excellence have been inherited through the history and philosophy of science in terms of basic principles, such as formalization, testing, replication, and dissemination. More specifically, the properties of Truth, Beauty, and Justice proposed by C.A. Lave and J.G. March for mathematical social science are equally valid criteria for assessing quality in social simulation models. Helpful as such classic standards of quality may be, social computing adds new scientific features (complex systems, object-oriented simulations, network models, emergent dynamics) that require development as additional standards for judging quality. Social simulation models in particular (e.g., agent-based modeling) contribute further specific requirements for assessing quality. This paper proposes and discusses a set of dimensions for discerning quality in social simulations, especially agent-based models, beyond the traditional standards of verification and validation.


Quality standards evaluation criteria social simulations agent-based models comparative analysis computational methodology Simon’s paradigm 


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© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Center for Social Complexity and Dept. Computational Social Science, Krasnow Institute for Advanced StudyGeorge Mason UniversityFairfaxUSA

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