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Published in:
2014 | OriginalPaper | Chapter
Generating Functionals for Guided Self-Organization
Author : Claudius Gros
Published in: Guided Self-Organization: Inception
Publisher: Springer Berlin Heidelberg
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One may take it as a running joke, that complex systems are complex since they are complex. It is however important to realize, this being said, that complex systems come in a large varieties, and in many complexity classes, ranging from relatively simple to extraordinary complex. One may distinguish in this context between classical and modern complex system theory. In the classical approach one would typically study a standardized model, like the Lorentz model or the logistic map, being described usually by maximally a handful of variables and parameters (Gros 2008). Many real-world systems are however characterized by a very large number of variables and control parameters, especially when it comes to biological and cognitive systems. It has been noted, in this context, that scientific progress may generically be dealing with complexity barriers of various severities, in far reaching areas like medicine and meteorology (Gros 2012b), when researching real-world natural or biological complex systems.