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Different Modelling Purposes

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Simulating Social Complexity

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

How one builds, checks, validates and interprets a model depends on its ‘purpose’. This is true even if the same model is used for different purposes, which means that a model built for one purpose but now used for another may need to be rechecked, revalidated and maybe even rebuilt in a different way. Here we review some of the different purposes for building a simulation model of complex social phenomena, focussing on five in particular: theoretical exposition, prediction, explanation, description and illustration. The chapter looks at some of the implications in terms of the ways in which the intended purpose might fail. In particular, it looks at the ways that a confusion of modelling purposes can fatally weaken modelling projects, whilst giving a false sense of their quality. This analysis motivates some of the ways in which these ‘dangers’ might be avoided or mitigated.

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Notes

  1. 1.

    With the exception of the purpose of description where a model is intended to reflect what is observed

  2. 2.

    He discusses ‘prediction’ and then lists 16 other reasons to model.

  3. 3.

    I am not ruling out the possibility of reusable model components in the future using some clever protocol; it is just that I have not seen any good cases of code reuse and many bad ones.

  4. 4.

    A later chapter (Chap. 28 (Edmonds et al. 2017)) takes a more fine-grained approach in the context of understanding human societies.

  5. 5.

    It would not really matter even if the code had a bug in it, if the code reliably predicts (though it might impact upon the knowledge of when we can rely upon it or not).

  6. 6.

    Where model B may be a random or null model but also might be a rival model

  7. 7.

    To be precise, some people have claimed to predict various social phenomena, but there are very few cases where the predictions are made public before the data is known and where the number of failed predictions can be checked. Correctly predicting events after they are known is much easier!

  8. 8.

    I am being a little disparaging here, it may be that these have a definite meaning in terms of relating different scales or some such, but too often, they do not have any clear meaning but just help the model fit stuff.

  9. 9.

    In the sense of not being vulnerable to being shown to be wrong later

  10. 10.

    To be precise, it does assume there are discrete entities or objects and that there are processes within these that can be represented in terms of computations, but these are not very restrictive assumptions.

  11. 11.

    Indeed, the work spawned a whole industry of papers doing just such an exploration.

  12. 12.

    Kuhn (1962) pointed out the tendency of scientists to only see the evidence that is coherent with an existing theory—it is as if they have ‘theoretical spectacles’ that filter out other kinds of evidence.

  13. 13.

    This does not include private modelling, whose purpose maybe playful or exploratory; however, in this case one should not present the results or model as if they have achieved anything more than illustration (to oneself). If one finds something of value in the exploration, it should then be redone properly for a particular purpose to be sure it is worth public attention.

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Acknowledgements

Many thanks to all those with whom I have discussed these matters, including Scott Moss, David Hales, Bridget Rosewell and all those who attended the workshop on validation held in Manchester.

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Correspondence to Bruce Edmonds .

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Further Reading

Further Reading

  • Epstein, J. M. (2008). Why model? Journal of Artificial Societies and Social Simulation, 11(4). 12. http://jasss.soc.surrey.ac.uk/11/4/12.html

  • This gives a brief tour of some of the reasons to simulate other than that of prediction.

  • Edmonds, B., Lucas, P., Rouchier, J., & Taylor, R. (2017). Understanding human societies. doi:https://doi.org/10.1007/978-3-319-66948-9_28.

  • In this chapter, some modelling purposes that are specific to human social phenomena are examined in more detail giving examples from the literature.

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Edmonds, B. (2017). Different Modelling Purposes. In: Edmonds, B., Meyer, R. (eds) Simulating Social Complexity. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-66948-9_4

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  • DOI: https://doi.org/10.1007/978-3-319-66948-9_4

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