David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
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.
|Keywords||Philosophy Philosophy Epistemology Logic Metaphysics Philosophy of Language|
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Wendy S. Parker (2009). Confirmation and Adequacy-for-Purpose in Climate Modelling. Aristotelian Society Supplementary Volume 83 (1):233-249.
Gregor Betz (2009). Underdetermination, Model-Ensembles and Surprises: On the Epistemology of Scenario-Analysis in Climatology. [REVIEW] Journal for General Philosophy of Science 40 (1):3 - 21.
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.
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Xavier de Donato Rodríguez & Jesús Zamora Bonilla (2009). Credibility, Idealisation, and Model Building: An Inferential Approach. [REVIEW] Erkenntnis 70 (1):101 - 118.
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