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Complexity: against systems

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Abstract

This article assumes a specific intuitive notion of complexity as a difficulty to generate and/or assess the plausibility of models. Based on this intuitive understanding of complexity, it identifies two main causes of complexity, namely, radical openness and contextuality. The former is the idea that there are no natural systems. The modeler always needs to draw artificial boundaries around phenomena to generate feasible models. Contextuality is intimately connected to the requirement to simplify models and to leave out most aspects. Complexity occurs when contextuality and radical openness cannot be contained that is when it is not clear where the boundaries of the system are and which abstractions are the correct ones. This concept of complexity is illustrated using a number of example from evolution.

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Notes

  1. The issue is not always quite as clear-cut. Particularly when it comes to large-scale computational models there can be significant problems to create a consensus on the properties of the model when it is run on different platforms, or even differently configured versions of the same platform. These problems certainly do exists, are interesting and indeed important to consider and are also relevant for complexity. However, as far as the following discussion is concerned, they are an unnecessary complication in that they do not interfere with the conclusion we will reach. We will therefore assume the simplest case that formal models are unproblematic.

  2. The various interpretations of Quantum Mechanics are an example of disagreements on the semantic models while there is an agreement on the syntactic models.

  3. It has to be pointed out that complexity is not Rosen’s primary interest, which is directed towards organizational principles of living systems. Complexity is more an accidental fallout rather than the main focus of his investigations. Hence he formulates complexity, rather specifically, in terms of abstract models of metabolic systems.

  4. This is not to be confused with the memory space the simulated objects take in th physical computer on which Tierra is implemented. This memory space, while practically of importance is of no consequence for the behavior of the model.

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Acknowledgments

The research for this article was partially funded by the Norwegian Research Council. The author gratefully acknowledges the hospitality of the Senter for Vitskapsteori at the University of Bergen (Norway) where parts of this manuscript were conceived and drafted.

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  1. School of Computing, University of Kent, CT2 7NF, Canterbury, United Kingdom

    Dominique Chu

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  1. Dominique Chu
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Chu, D. Complexity: against systems. Theory Biosci. 130, 229–245 (2011). https://doi.org/10.1007/s12064-011-0121-4

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