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.
Original language | English |
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Pages (from-to) | 301-320 |
Number of pages | 19 |
Journal | The Monist |
Volume | 97 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2014 |
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Professor Seth Bullock
- Department of Computer Science - Toshiba Chair in Data Science and Simulation
Person: Academic