David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Synthese 152 (1):1 - 19 (2006)
In computer simulations of physical systems, the construction of models is guided, but not determined, by theory. At the same time simulations models are often constructed precisely because data are sparse. They are meant to replace experiments and observations as sources of data about the world; hence they cannot be evaluated simply by being compared to the world. So what can be the source of credibility for simulation models? I argue that the credibility of a simulation model comes not only from the credentials supplied to it by the governing theory, but also from the antecedently established credentials of the model building techniques employed by the simulationists. In other words, there are certain sorts of model building techniques which are taken, in and of themselves, to be reliable. Some of these model building techniques, moreover, incorporate what are sometimes called “falsifications.” These are contrary-to-fact principles that are included in a simulation model and whose inclusion is taken to increase the reliability of the results. The example of a falsification that I consider, called artificial viscosity, is in widespread use in computational fluid dynamics. Artificial viscosity, I argue, is a principle that is successfully and reliably used across a wide domain of fluid dynamical applications, but it does not offer even an approximately “realistic” or true account of fluids. Artificial viscosity, therefore, is a counter-example to the principle that success implies truth – a principle at the foundation of scientific realism. It is an example of reliability without truth.
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References found in this work BETA
Paul Horwich (2005). Truth. In Frank Jackson & Michael Smith (eds.), Erkenntnis. Oxford University Press 261-272.
Arthur Fine (1996). The Shaky Game: Einstein, Realism, and the Quantum Theory. University of Chicago Press.
Eric Winsberg (2003). Simulated Experiments: Methodology for a Virtual World. Philosophy of Science 70 (1):105-125.
Eric Winsberg (1999). Sanctioning Models: The Epistemology of Simulation. Science in Context 12 (2).
Arthur Fine (1991). Piecemeal Realism. Philosophical Studies 61 (1-2):79 - 96.
Citations of this work BETA
Wendy S. Parker (2009). Confirmation and Adequacy-for-Purpose in Climate Modelling. Aristotelian Society Supplementary Volume 83 (1):233-249.
Eric Winsberg (2009). Computer Simulation and the Philosophy of Science. Philosophy Compass 4 (5):835-845.
Joel Katzav, Henk A. Dijkstra & A. T. J. de Laat (2012). Assessing Climate Model Projections: State of the Art and Philosophical Reflections. Studies in History and Philosophy of Science Part B 43 (4):258-276.
Gregor Betz (2015). Are Climate Models Credible Worlds? Prospects and Limitations of Possibilistic Climate Prediction. European Journal for Philosophy of Science 5 (2):191-215.
Eric Winsberg (2006). Handshaking Your Way to the Top: Simulation at the Nanoscale. Philosophy of Science 73 (5):582-594.
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