David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
Learn more about PhilPapers
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|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
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.
Similar books and articles
Nigel Gilbert & Pietro Terna (2000). How to Build and Use Agent-Based Models in Social Science. Mind and Society 1 (1):57-72.
Axel Gelfert, Simulating Many-Body Models in Physics: Rigorous Results, 'Benchmarks', and Cross-Model Justification.
Gregory M. Mikkelson (2001). Complexity and Verisimilitude: Realism for Ecology. [REVIEW] Biology and Philosophy 16 (4):533-546.
Alexander Rueger (2005). Perspectival Models and Theory Unification. British Journal for the Philosophy of Science 56 (3):579-594.
Mr Peter R. Krebs, Smoke Without Fire: What Do Virtual Experiments in Cognitive Science Really Tell Us?
Keith R. Sawyer (2004). Social Explanation and Computational Simulation. Philosophical Explorations 7 (3):219 – 231.
Eric B. Winsberg (2010). Science in the Age of Computer Simulation. The University of Chicago Press.
Stephan Hartmann (1996). The World as a Process: Simulations in the Natural and Social Sciences. In Rainer Hegselmann (ed.), Modelling and Simulation in the Social Sciences from the Philosophy of Science Point of View.
Added to index2009-01-28
Total downloads124 ( #32,497 of 1,934,364 )
Recent downloads (6 months)14 ( #39,220 of 1,934,364 )
How can I increase my downloads?