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Simulation and Calibration: Mitigating Uncertainty

Published online by Cambridge University Press:  01 January 2022

Abstract

Calibrating a simulation is a crucial step for certain kinds of simulation modeling, and it results in a simulation that is epistemically different from its pre- or uncalibrated counterpart. This article discusses how simulation model builders mitigate uncertainty about model parameters that are necessary for modeling through calibration and argues that the simulation outcomes after calibration are physically meaningful and relevant. When evaluating the epistemic status of computer simulations, comparisons between computer simulations and traditional experiments need to consider this important methodological step.

Type
Computer Simulation and Computer Science
Copyright
Copyright 2021 by the Philosophy of Science Association. All rights reserved.

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Footnotes

Many thanks to those at the University of Illinois at Chicago’s Beyond Spacetime research group, Women in Philosophy at Northwestern University, Models and Simulations 8 at the University of South Carolina, and the German Research Foundation Research Training Group 2073’s October 2019 Research Colloquium at Universität Bielefeld, where versions of this article were presented. I would also like to thank the PSA’s anonymous reviewers, as well as Martin Carrier, Torsten Wilholt, and Mathias Frisch, for their comments and suggestions. I am very grateful to Robert Will for our many conversations about reservoir simulations, to Daniel Skibra for numerous discussions, and to Nick Huggett for his input on many drafts of this article.

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