Summary
The present chapter deals with chance discovery from the perspective of complex systems. We will limit ourselves to a type of complex systems known as self-organized critical systems; to discuss these systems we need to make clear what we mean by notions such as complex, scale free, critical, and self-organization. To fix some ideas we will introduce two self-organizing complex models, i.e. a simple cellular automaton model and a model of evolutionary ecology. This highlights how seemingly innocent local perturbations may propagate through the entire system, totally altering the composition of the system. We consider the possibility of prediction in complex systems, and elaborate on the specifics of chance discovery in interconnected and highly sensitive complex systems.
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© 2003 Springer-Verlag Berlin Heidelberg
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Jensen, H.J. (2003). Self-organizing Complex Systems. In: Ohsawa, Y., McBurney, P. (eds) Chance Discovery. Advanced Information Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06230-2_4
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DOI: https://doi.org/10.1007/978-3-662-06230-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05609-3
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