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Complex Adaptive Systems

Page, Scott, and John H. Miller. 2007. Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton: Princeton University Pres.

This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field’s leading authorities. Such systems–whether political parties, stock markets, or ant colonies–present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents.

Reading level: Basic

Previously, I reviewed Frontiers of Complexity, an early book to describe the application of computational methods to explore complexity the hard sciences. This more recent book, Complex Adaptive Systems by John Miller and Scott Page, takes a similar approach but focuses on the social sciences instead.

Both authors have been associated with the Santa Fe Institute. Since 1984, the Santa Fe Institute has been a multidisciplinary, multi-sector research and education center digging into complex challenges. It does complex systems research, which attempts to uncover and understand the deep commonalities that link artificial, human, and natural systems.

Miller and Page present a central theme of “in-between” the usual scientific boundaries, namely in between

  • various scientific fields, where problems such as organization, adaptation and robustness transcend all of these;
  • stasis and chaos, control and anarchy. The world tends to exist in between these extremes, whereas traditional scientific methods have positioned themselves at or approaching the extremes,e.g. equilibrium models.

The core material in this book is about computational agent-based models, one of the fundamental tools for exploring complex behavior. It was and still is a great primer on the subject. For many folks, Complex Adaptive Systems was one of the first books they bought once they heard about these ideas. I was one. Other than exposure to agent-based modeling, what I really learned from this book was that the theories of complex adaptive systems were more pertinent to real life than either the scientific management or statistics courses had taught me when I did my MBA. Basically, this is because life lies well in between the perfect reductive or stochastic worlds upon which most education is based.

The study of complex systems attempts to illuminate the interest in between our usual scientific boundaries, and in so doing, paradoxes abound. It is the study of how the few are different from the one or the infinite. It is the exploration of time in a highly choreographed dance. It is a search for tight connections in a loosely coupled world. It is the precise characterization of when the details do not matter. Modeling, by its very nature, is about extremes. Unfortunately, sometimes in the pursuit of extremes we kill off the most interesting parts of the world – “water which is too pure has no fish”.