Abstract
To provide an introduction to this book, we explain the motivation to publish this volume, state its main goal, characterize its intended readership, and give an overview of its content. To this purpose, we briefly summarize each chapter and put it in the context of the whole volume. We also take the opportunity to stress connections between the chapters. We conclude with a brief outlook.
The main motivation to publish this volume was the diagnosis that the validation of computer simulation needs more attention in practice and in theory. The aim of this volume is to improve our understanding of validation. To this purpose, computer scientists, mathematicians, working scientists from various fields, as well as philosophers of science join efforts. They explain basic notions and principles of validation, embed validation in philosophical frameworks such as Bayesian epistemology, detail the steps needed during validation, provide best practice examples, reflect upon challenges to validation, and put validation in a broader perspective. As we suggest in our outlook, the validation of computer simulations will remain an important research topic that needs cross- and interdisciplinary efforts. A key issue is whether, and if so, how very rigorous approaches to validation that have proven useful in, e.g., engineering can be extended to other disciplines.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Augusiak, J., Van den Brink, P. J., & Grimm, V. (2014). Merging validation and evaluation of ecological models to ‘evaludation’: A review of terminology and a practical approach. Ecological Modelling, 280, 117–128.
Godfrey-Smith, P. (2003). Theory and reality. An introduction to the philosophy of science. Chicago: University of Chicago Press.
Feinstein, A. H., & Cannon, H. M. (2003). A hermeneutical approach to external validation of simulation models. Simulation & Gaming, 34, 186–197.
Frigg, R., Bradley, S., Du, H., & Smith, L. A. (2014). Laplace’s demon and the adventures of his apprentices. Philosophy of Science, 81(1), 31–59.
Frigg, R., & Reiss, J. (2009). The philosophy of simulation: Hot new issues or same old stew? Synthese, 169(3), 593–613.
Ghetiu, T., Polack, F. A., & Bown, J. (2010). Argument-driven validation of computer simulations–A necessity rather than an option. In VALID 2010. The Second International Conference on Advances in System Testing and Validation Lifecycle, August 22–27 (pp. 1–4). Nice, France, IEEE Press.
Goldman, Alvin I. (1999). Knowledge in a social world. Oxford: Clarendon Press.
Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., et al. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310, 987–991.
Harding, A., Keegan, M., & Kelly, S. (2010). Validating a dynamic population microsimulation model: Recent experience in Australia. International Journal of Microsimulation, 3(2), 46–64.
Hartmann, S. (1996). The world as a process: Simulations in the natural and social sciences. In: R. Hegselmann, U. Müller, & K. G. Troitzsch, (Eds.), Modelling and simulation in the social sciences from the philosophy of science point of view, theory and decision library (pp. 77–100). Dordrecht: Kluwer.
Herskovitz, P. J. (1991). A theoretical framework for simulation validation: Popper’s falsificationism. International Journal of Modelling and Simulation, 11, 56–58.
Humphreys, P. (2004). Extending ourselves: Computational science, empiricism, and scientific method. New York: Oxford University Press.
IPCC. (2014). Climate change 2013–The physical science basis working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.
Kaldor, N. (1968). Capital accumulation and economic growth. In F. A. Lutz & D. C. Hague (Eds.), The theory of capital (Reprint ed., pp. 177–222). London: Macmillan.
Kertész, A. (1993). Artificial intelligence and the sociology of scientific knowledge. Frankfurt/M.: Lang.
Klein, E. E., & Herskovitz, P. J. (2005). Philosophical foundations of computer simulation validation. Simulation & Gaming, 36, 303–329.
Kleindorfer, G. B., O’Neill, L., & Ganeshan, R. (1998). Validation in simulation: Various positions in the philosophy of science. Management Science, 44, 1087–1099.
Murray-Smith, D. J. (2015). Testing and validation of computer simulation models: Principles methods and applications. Cham: Springer.
Nickles, T. (1989). Integrating the science studies disciplines. In S. Fuller, M. de Mey, T. Shinn, & S. Woolgar (Eds.), The cognitive turn. Sociological and psychological perspectives on science (pp. 225–256). Dordrecht: Kluwer.
Oberkampf, W. L., & Roy, C. J. (2010). Verification and validation in scientific computing. Cambridge: Cambridge University Press.
Oreskes, N., Shrader-Frechette, K., & Belitz, K. (1994). Verification, validation, and confirmation of numerical models in the earth sciences. Science, 263, 641–646.
Parker, W. S. (2008). Franklin, holmes, and the epistemology of computer simulation. International Studies in the Philosophy of Science, 22(2), 165–183.
Parker, W. S. (2009). Confirmation and adequacy-for-purpose in climate modeling. Aristotelian Society Supplementary, 83, 233–249.
Roache, P. J. (2009). Fundamentals of verification and validation. New Mexico: Hermosa Publishers.
Rudner, R. (1953). The scientist qua scientist makes value judgments. Philosophy of Science, 20, 1–6.
Schlesinger, S., et al. (1979). Terminology for model credibility. Simulation, 32, 103–104.
Walker, D. C., Hill, G., & Wood, S. M. et al. (2 more authors). (2004). Agent-based computational modeling of wounded epithelial cell monolayers. IEEE Transactions on Nanobioscience, 3(3), 153–163.
Winsberg, E. (2001). Simulations, models, and theories. Complex physical systems and their representations. Philosophy of Science, 68, S442–S454.
Winsberg, E. (2010). Science in the age of computer simulation. Chicago: University of Chicago Press.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Beisbart, C., Saam, N.J. (2019). Introduction: Computer Simulation Validation. In: Beisbart, C., Saam, N. (eds) Computer Simulation Validation. Simulation Foundations, Methods and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-70766-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-70766-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70765-5
Online ISBN: 978-3-319-70766-2
eBook Packages: Computer ScienceComputer Science (R0)