When considering the history of complexity science and related theory, it is difficult to bypass the wide-ranging narrative Melanie Mitchell (2009) provides on the subject. Arguably, complex systems have been studied by humanity for thousands of years. Mitchell (2009) traces this journey back to Aristotle (384-322 B.C.) and the emergence of Dynamical Systems Theory and how this influenced thinking and scientific discovery in the ages to come, until the sixteenth century and the contradicting studies of Galileo on motion. Nonetheless, Mitchell (2009:17) points to Isaac Newton as the “most important person in the history of dynamics” and the inventor of the science of dynamics. Based on Newtonian mechanics, Laplace proclaimed in 1814 that it is possible to predict anything.
However, the twentieth century saw the emergence of contradictory discoveries to this notion of absolute prediction, with an increasing understanding of chaos and chaotic systems and the concept of “sensitive dependence on initial conditions”. However, the first experience of a chaotic system occurred in the late nineteenth century already, when the French mathematician Henri Poincare modelled weather behaviour. This occurrence paved the way for the aspiration of predicting weather over a longer period and Edward Lorenz found in 1963 that even simpler computational weather models are subject to the sensitive dependence on initial conditions, with these systems manifesting nonlinearity.
From this theory of chaos emerged complexity theory and although complex systems were researched explicitly since the 1970’s (Vemuri, 1978), the studying of complex systems gained much traction with the establishment of the Santa Fe Institute, the first research institute dedicated to research of complex systems and especially complex adaptive systems. The institute was founded by a group of 24 scientists and mathematicians, with a number of these individuals being scientists with Los Alamos National Laboratory. In later years a number of other institutions were formed, dedicated to the study of complexity in systems which range from biological to social and economic systems.
I acknowledge that this discussion provides the briefest of overviews on the subject of complex systems and the Further Reading section presents a number of resources on the subject. Furthermore, this map by Castellani (2018) provides a great visual overview of the development of the complexity sciences over a number of decades.
Castellani, B. (2018) Map of the Complexity Sciences. Art & Science Factory. https://www.art-sciencefactory.com/complexity-map_feb09.html
Laplace, P. S. (1814). Essai Philosophique Sur Les Probabilites. Paris: Courcier.
Mitchell, M. (2009). Complexity: A Guided Tour. Oxford, U.K.: Oxford University Press.
Vemuri, V. (1978). Modeling of Complex Systems: An Introduction. New York: Academic Press.