How simulations fail

Synthese 190 (12):2367-2390 (2011)
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‘The problem with simulations is that they are doomed to succeed.’ So runs a common criticism of simulations—that they can be used to ‘prove’ anything and are thus of little or no scientific value. While this particular objection represents a minority view, especially among those who work with simulations in a scientific context, it raises a difficult question: what standards should we use to differentiate a simulation that fails from one that succeeds? In this paper we build on a structural analysis of simulation developed in previous work to provide an evaluative account of the variety of ways in which simulations do fail. We expand the structural analysis in terms of the relationship between a simulation and its real-world target emphasizing the important role of aspects intended to correspond and also those specifically intended not to correspond to reality. The result is an outline both of the ways in which simulations can fail and the scientific importance of those various forms of failure.


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Author Profiles

Patrick Grim
University of Michigan, Ann Arbor
Adam Rosenfeld
University of North Carolina, Greensboro
Robert Rosenberger
Georgia Institute of Technology

References found in this work

How the laws of physics lie.Nancy Cartwright - 1983 - New York: Oxford University Press.
Models in Science (2nd edition).Roman Frigg & Stephan Hartmann - 2021 - The Stanford Encyclopedia of Philosophy.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - New York: Cambridge University Press.
The scientific image.C. Van Fraassen Bas - 1980 - New York: Oxford University Press.

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