Identifying Self-Organization and Adaptability in Complex Adaptive Systems

Self-organization and adaptability are critical properties of complex adaptive systems (CAS), and their analysis provides insight into the design of these systems, consequently leading to real-world advancements. However, these properties are difficult to analyze in real-world scenarios due to performance constraints, metric design, and limitations in existing modeling tools. Several metrics have been proposed for their identification, but metric effectiveness under the same experimental settings has not been studied before. In this paper we present an observation tool, part of a complex adaptive systems modeling framework, that allows for the analysis of these metrics for large-scale complex models. We compare and contrast a wide range of metrics implemented in our observation tool. Our experimental analysis uses the classic model of Game of Life to provide a baseline for analysis, and a more complex Emergency Department model to further explore the suitability of these metrics and the modeling and analysis challenges faced when using them.

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