David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophy of Science 74 (5):873-883 (2007)
As scientists begin to study increasingly complex questions, many have turned to computer simulation to assist in their inquiry. This methodology has been challenged by both analytic modelers and experimentalists. A primary objection of analytic modelers is that simulations are simply too complicated to perform model verification. From the experimentalist perspective it is that there is no means to demonstrate the reality of simulation. The aim of this paper is to consider objections from both of these perspectives, and to argue that a proper understanding and application of robustness analysis is able to resolve them. ‡The author would like to thank Cristina Bicchieri, Michelle Foa, Paul Humphreys and Michael Weisberg for their helpful comments and suggestions. †To contact the author, please write to: Department of Philosophy, University of Pennsylvania, 433 Logan Hall, 249 S. 36th Street, Philadelphia, PA, 19104-6304; e-mail: email@example.com.
|Keywords||Simulation Robustness Modeling|
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Citations of this work BETA
Wendy S. Parker (2011). When Climate Models Agree: The Significance of Robust Model Predictions. Philosophy of Science 78 (4):579-600.
Elisabeth A. Lloyd (2010). Conﬁrmation and Robustness of Climate Models. Philosophy of Science 77 (5):971–984.
Ryan Muldoon, Tony Smith & Michael Weisberg (2012). Segregation That No One Seeks. Philosophy of Science 79 (1):38-62.
Elisabeth A. Lloyd (2009). Varieties of Support and Confirmation of Climate Models. Aristotelian Society Supplementary Volume 83 (1):213-232.
Armin W. Schulz (2015). The Heuristic Defense of Scientific Models: An Incentive-Based Assessment. Perspectives on Science 23 (4):424-442.
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