Change and identity in complex systems
| Abstract | Complex systems are dynamic and may show high levels of variability in both space and time. It is often difficult to decide on what constitutes a given complex system, i.e., where system boundaries should be set, and what amounts to substantial change within the system. We discuss two central themes: the nature of system definitions and their ability to cope with change, and the importance of system definitions for the mental metamodels that we use to describe and order ideas about system change. Systems can only be considered as single study units if they retain their identity. Previous system definitions have largely ignored the need for both spatial and temporal continuity as essential attributes of identity. After considering the philosophical issues surrounding identity and system definitions, we examine their application to modeling studies. We outline a set of five alternative metamodels that capture a range of the basic dynamics of complex systems. Although Holling’s adaptive cycle is a compelling and widely applicable metamodel that fits many complex systems, there are systems that do not necessarily follow the adaptive cycle. We propose that more careful consideration of system definitions and alternative metamodels for complex systems will lead to greater conceptual clarity in the field and, ultimately, to more rigorous research. | |||||||||
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A. Gecow & A. Hoffman (1983). Self-Improvement in a Complex Cybernetic System and its Implications for Biology. Acta Biotheoretica 32 (1).
Kara Vander Linden (2006). A Grounded Approach to the Study of Complex Systems. World Futures 62 (7):491 – 497.
Meinard Kuhlmann (2011). Mechanisms in Dynamically Complex Systems. In Phyllis McKay Illari & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press.
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