Understanding the ecology of complex adaptive systems, such as organisms, societies, and languages, poses many challenges. A thorough understanding of all of the individual components necessitates an understanding of the system as a whole, given that the whole system is more than the sum of its parts. Dr Chris Girard, Associate Professor of Sociology with the Department of Global and Sociocultural Studies at Florida International University, has developed an evolutionary model: coevolving informatics. This paradigm offers a transdisciplinary approach to understanding complex adaptive systems. Throughout this research, Dr Girard adopts an informatics perspective, employing complexity and evolutionary theories to examine the processing of information within natural and artificial systems.

Three coevolving dimensions

Dr Girard explains how complex adaptive systems are made up of three coevolving dimensions: spatial boundaries, thermodynamic-economic specialisation, and signal processing, which are central to major transitions in evolution.

Spatial boundaries
When a system becomes more complex, its spatial boundaries are realigned. These systems undergo extensive growth, increasing their size, or the number of component parts, which in turn increases the system’s complexity. Consequently, the system’s spatial boundaries go through an intensive process of realignment, resulting in the system boundaries becoming more open or porous.

Thermoeconomics
In line with thermodynamic-economics specialisation, when a system’s complexity increases so does the exchange of resources required in order for the system to grow and reproduce. Initially, during the extensive phase, these exchanges tend to be vertical, or hierarchical. Later, the system moves into the intensive phase and these exchanges become progressively more horizontal.

Signal processing
When entities interact with each other they produce new information, or signals, increasing the system’s total information. The system’s signal processing facilitates its adaptation to a changing environment. Dr Girard comments: “Indeed, major evolutionary transitions in complex adaptive systems are based on new ways of storing, transmitting and processing information. Most significantly, this transformation allows information processing to become more independent from physical location.”