2026-06-01T03:18:35Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/76352023-04-11T00:05:21Zcom_10259_3830com_10259_5086com_10259_2604col_10259_3832

00925njm 22002777a 4500 dc Mauhe, Nicolas author Izquierdo Millán, Luis Rodrigo author Izquierdo, Segismundo S. author 2023-03 This paper discusses a prominent way in which social simulations can contribute (and have contributed) to the advance of science; namely, by refuting some of our incorrect 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. Indeed, here we argue that this is a role that many well-known social simulation models have played, and it may be one of the main reasons why such well-known models have become so popular. To test this hypothesis, here we examine several popular models in the social simulation literature and 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 have greatly advanced science and, in some cases, have even opened a new field of research. 1460-7425 http://hdl.handle.net/10259/7635 10.18564/jasss.5076 1460-7425 Social Simulation Computer Simulation Refutation Modelling Counter-Example Markov Chain Social Simulation Models as Refuting Machines