Abstract

What is it about simulation models that has led some practitioners to treat them as potential sources of empirical data on the real-world systems being simulated; that is, to treat simulations as ‘artificial worlds’within which to perform computational ‘experiments’? Here we use the work of Richard Levins as a starting point in identifying the appeal of this model building strategy, and proceed to account for why this appeal is strongest for computational modellers. This analysis suggests a perspective on simulation modelling that makes room for ‘artificial worlds’ as legitimate science without having to accept that they should be treated as sources of empirical data