Social Simulation Models as Refuting Machines

Nicolas Mauhe (), Luis R. Izquierdo () and Segismundo S. Izquierdo ()
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Luis R. Izquierdo: http://luis.izqui.org
Segismundo S. Izquierdo: http://www.segis.izqui.org/

Journal of Artificial Societies and Social Simulation, 2023, vol. 26, issue 2, 8

Abstract: This paper discusses a prominent way in which social simulations can contribute -and have contributed- to the advancement of Science, namely, by refuting some of our (wrong) beliefs about how the real world works. More precisely, social simulations can produce counter-examples that reveal something is wrong in a prevailing scientific assumption. In fact, in this paper we argue that this is a role that many well-known social simulation models in the literature have played and, arguably, it may be one of the main reasons why such well-known models became so popular. To test this hypothesis, in this paper we examine several popular models in the Social Simulation literature and indeed we find that all these models are most naturally interpreted as providers of compelling and reproducible (computer-generated) evidence that refuted some assumption or belief in a prevailing theory. By refuting prevailing theories, these models greatly advanced Science and, in some cases, they even opened up a new research field.

Keywords: Social Simulation; Computer Simulation; Refutation; Modelling; Counter-Example; Markov Chain (search for similar items in EconPapers)
Date: 2023-03-31
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Citations: View citations in EconPapers (1)

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