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Simulated Experiments: Methodology for a Virtual World

Published online by Cambridge University Press:  01 January 2022

Abstract

This paper examines the relationship between simulation and experiment. Many discussions of simulation, and indeed the term “numerical experiments,” invoke a strong metaphor of experimentation. On the other hand, many simulations begin as attempts to apply scientific theories. This has lead many to characterize simulation as lying between theory and experiment. The aim of the paper is to try to reconcile these two points of view—to understand what methodological and epistemological features simulation has in common with experimentation, while at the same time keeping a keen eye on simulation's ancestry as a form of scientific theorizing. In so doing, it seeks to apply some of the insights of recent work on the philosophy of experiment to an aspect of theorizing that is of growing philosophical interest: the construction of local models.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

I thank Arthur Fine, Mathias Frisch, Karen Darling, and Joanne Waugh for their comments and criticisms, as well as many people who offered helpful comments when I presented earlier versions of this paper at the University of South Florida and at Wichita State University. I am greatly indebted to three anonymous reviewers—especially one, whose efforts went well beyond the norm.

References

Bate, R., Mueller, J., and White, D. (1971), Fundamentals of Astrodynamics. New York: Dover.Google Scholar
Cartwright, Nancy (1983), How the Laws of Physics Lie. Oxford: Oxford University Press.CrossRefGoogle Scholar
Cartwright, Nancy (1999), The Dappled World: A Study of the Boundaries of Science. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Dowling, D. (1999), “Experimenting on Theories”, Experimenting on Theories 12 (2): 261–73..Google Scholar
Franklin, Allan (1986), The Neglect of Experiment. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Galison, Peter (1996), “Computer Simulations and the Trading Zone”, in Galison, P. and Stump, D. (eds.), The Disunity of Science: Boundaries, Contexts, and Power. Stanford: Stanford University Press.Google Scholar
Galison, Peter (1997), Image and Logic: A Material Culture of Microphysics. Chicago: University of Chicago Press.Google Scholar
Giere, Ronald N. (1999), Science Without Laws. Chicago: University of Chicago Press.Google Scholar
Hacking, Ian (1983), Representing and Intervening: Introductory Topics in the Philosophy of Science. New York: Free Press.CrossRefGoogle Scholar
Hacking, Ian (1988), “On the Stability of the Laboratory Sciences”, On the Stability of the Laboratory Sciences 85 (10): 507–15..Google Scholar
Hacking, Ian (1992) “Do Thought Experiments Have a Life of Their Own?”, in Fine, A., Forbes, M., and Okruhlik, K., (eds.), PSA 1992, Vol. 2. East Lansing, MI: The Philosophy of Science Association, 302310.Google Scholar
Hughes, R. (1999), “The Ising Model, Computer Simulation, and Universal Physics”, in Morgan, Mary and Morrison, Margaret (eds.), Models as Mediators. Cambridge: Cambridge University Press.Google Scholar
Humphreys, Paul (1991). “Computer Simulation”, in Fine, A., Forbes, M., and Wessels, L. (eds.), PSA 1990, Vol. 2. East Lansing MI: The Philosophy of Science Association, 497506.Google Scholar
Humphreys, Paul (1994), “Numerical Experimentation”, in Paul Humphreys (ed.), Patrick Suppes: Scientific Philosopher, Vol. 2 of Philosophy of Physics, Theory Structure, Measurement Theory, Philosophy of Language, and Logic. Dordrecht: Kluwer Academic Publishers.Google Scholar
Humphreys, Paul (1995), “Computational Science and Scientific Method”, Computational Science and Scientific Method 5 (1): 499512..Google Scholar
Kaufmann, W.J., and Smarr, L.L. (1993), Supercomputing and the Transformation of Science. New York: Scientific American Library.Google Scholar
Marion, Mathieu (1998), Wittgenstein, Finitism, and the Foundations of Mathematics. Oxford: Clarendon Press.Google Scholar
Morgan, Mary, and Morrison, Margaret (eds.) (1999), Models as Mediators. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Newell, A., and Simon, H. A. (1976), “Computer Science as Empirical Enquiry”, Computer Science as Empirical Enquiry 19:113126.Google Scholar
Norton, S., and Suppe, F. (2000), “Why Atmospheric Modeling is Good Science”, in Miller, C. and Edwards, P. (eds.), Changing the Atmosphere: Expert Knowledge and Environmental Governance. Cambridge, MA: MIT Press.Google Scholar
Rohrlich, Fritz (1991), “Computer Simulation in the Physical Sciences”, PSA 1990, Vol. 2. East Lansing, MI: The Philosophy of Science Association, 507–18.Google Scholar
Weissert, T. (1997), The Genesis of Simulation in Dynamics: Pursuing the Fermi-Pasta-Ulam Problem. New York: Springer.CrossRefGoogle Scholar
Winkler, K., Chalmers, J., Hodson, S., Woodward, P., Zabusky, N. (1987), “A Numerical Laboratory”, A Numerical Laboratory 40 (10): 2837..Google Scholar
Winsberg, Eric (1999), “Sanctioning Models: The Epistemology of Simulation”, Sanctioning Models: The Epistemology of Simulation 12(2): 275292.Google Scholar
Winsberg, Eric (1999a) Simulation and the Philosophy of Science: Computationally Intensive Studies of Complex Physical Systems, Ph.D. Dissertation, Bloomington: Indiana University.Google Scholar
Winsberg, Eric (2001) “Simulations, Models, and Theories: Complex Physical Systems and Their Representations”, Philosophy of Science 68 (Proceedings): S442S454.CrossRefGoogle Scholar
Woodward, P., and Collela, P. (1984), “The Numerical Simulation of Two-Dimensional Gas Flows with Strong Shocks”, The Numerical Simulation of Two-Dimensional Gas Flows with Strong Shocks 54:115–43.Google Scholar
Zabusky, N. (1987), “Grappling with Complexity”, Grappling with Complexity 40 (10): 2527.Google Scholar