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Simulating Thomas Kuhn’s Scientific Revolutions: The Example of the Paradigm Change from Systems Dynamics to Agent Based Modelling

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Advances in Social Simulation 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 528))

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Abstract

Based on evolutionary game theory, this paper presents a model that allows to reproduce different patterns of change of the main paradigm of a scientific community. One of these patterns is the classical scientific revolution of Thomas Kuhn (The Structure of Scientific Revolutions. University of Chicago Press, Chicago 1962), which completely replaces an old paradigm by a new one. Depending on factors like the acceptance rate of extra-paradigmatic works by the reviewers of scientific journals, there are however also other forms of change, which may e.g. lead to the coexistence of an old and a new paradigm. After analysing the different types of paradigm-changes and the conditions of their occurrence by means of EXCEL based simulation runs, the article explores the applicability of the model to a particular case: the spread of agent based modelling at the expense of the older systems dynamics approach. For the years between 1993 and 2012 the model presented in this article reproduces the observed bibliometric data remarkably well: it thus seems to be empirically confirmed.

This is a substantially enlarged and improved version of an article in German language, published by the same author: G. Mueller, Die Krise der wissenschaftlichen Routine. In: Verhandlungen des 37. Kongresses der Deutschen Gesellschaft für Soziologie. http://www. publikationen.soziologie.de. Bochum, 2015.

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Notes

  1. 1.

    From (5a) and (5b) follows ΔS n  = −ΔS o such that the sum S n +S o is time-invariant and always yields 1 (see formula (1b)).

  2. 2.

    By definition A e  = 0 and E o  = 0 are the lowest possible values of these two parameters. Similarly, since A e  ≤ A i  = 1 and E o  ≤ E n  = 1, A e and E o cannot exceed the value 1.

  3. 3.

    P n + P o = (F n \( \raisebox{2pt}{$\scriptstyle*$} \)S n ) / (F n \( \raisebox{2pt}{$\scriptstyle*$} \)S n + F o \( \raisebox{2pt}{$\scriptstyle*$} \)S o ) + (F o \( \raisebox{2pt}{$\scriptstyle*$} \)S o ) / (F n \( \raisebox{2pt}{$\scriptstyle*$} \)S n + F o \( \raisebox{2pt}{$\scriptstyle*$} \)S o )= (F n \( \raisebox{2pt}{$\scriptstyle*$} \)S n + F o \( \raisebox{2pt}{$\scriptstyle*$} \)S o ) / (F n \( \raisebox{2pt}{$\scriptstyle*$} \)S n + F o \( \raisebox{2pt}{$\scriptstyle*$} \)S o ) = 1

  4. 4.

    Model-fit = Square root of (Sum of squares between observed and simulated P n /20) = 0.0041

  5. 5.

    As explained earlier in Sect. 3.1, A e  = 1 is a relative and not an absolute acceptance rate.

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Authors and Affiliations

  1. University of Fribourg, Pérolles 90, Fribourg, CH-1700, Switzerland

    Georg P. Mueller

Authors
  1. Georg P. Mueller
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Correspondence to Georg P. Mueller .

Editor information

Editors and Affiliations

  1. University College Groningen, University of Groningen, Groningen, The Netherlands

    Wander Jager

  2. Faculty of Mathematics and Natural Sciences, Institute of Artificial Intelligence, University of Groningen, Groningen, The Netherlands

    Rineke Verbrugge

  3. Faculty for Social and Behavioural Sciences, Department of Sociology, University of Groningen, Groningen, The Netherlands

    Andreas Flache

  4. Faculty of Spatial Sciences, Department of Spatial Planning and Environment, University of Groningen, Groningen, The Netherlands

    Gert de Roo

  5. Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands

    Lex Hoogduin

  6. Faculty of Mathematics and Natural Sciences, Department of Behavioural Ecology and Self-organisation, University of Groningen, Groningen, The Netherlands

    Charlotte Hemelrijk

A.1 Data Appendix

A.1 Data Appendix

Table A1 Numbers and shares of publications in the agent based modelling paradigm and the systems dynamics paradigm
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Mueller, G.P. (2017). Simulating Thomas Kuhn’s Scientific Revolutions: The Example of the Paradigm Change from Systems Dynamics to Agent Based Modelling. In: Jager, W., Verbrugge, R., Flache, A., de Roo, G., Hoogduin, L., Hemelrijk, C. (eds) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing, vol 528. Springer, Cham. https://doi.org/10.1007/978-3-319-47253-9_25

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  • DOI: https://doi.org/10.1007/978-3-319-47253-9_25

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  • Online ISBN: 978-3-319-47253-9

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