1 Introduction2 History and Origins: Intellectual FiguresMurray Gell-MannJohn HollandStuart KauffmanIlya PrigogineBrian Goodwin3 Attributes of CAS3.1 Distributed Control3.2 Connectivity3.3 Co-evolution3.4 Sensitive Dependence on Initial Conditions3.5 Emergent Order3.6 Far From Equilibrium3.7 State of Paradox4 Tools for CAS5 Evaluation: Application of CAS to Engineering Systems6 Conclusions6.1 Resources for Further InterestReferences1 Complex Adaptive Systems Serena Chan ESD.83 Research Seminar in Engineering Systems October 31, 2001/November 6, 2001 1 Introduction Complexity theory is a relatively new field that began in the mid-1980s at the Santa Fe Institute in New Mexico. Work at the Santa Fe Institute is usually presented as the study of Complex Adaptive Systems (CAS). The CAS movement is predominantly American, as opposed to the European “natural science” tradition in the area of cybernetics and systems. Like in cybernetics and systems theory, CAS shares the subject of general properties of complex systems across traditional disciplinary boundaries. However, CAS is distinguished by the extensive use of computer simulations as a research tool, and an emphasis on systems, such as markets or ecologies, which are less integrated or “organized” than the ones studied by the older tradition (e.g., organisms, machines and companies). 1.1 What is Complexity? Complexity results from the inter-relationship, inter-action and inter-connectivity of elements within a system and between a system and its environment. Murray Gell-Mann, in “Complexity” Vol. 1, No. 5, 1995/96, traces the meaning of complexity to the root of the word. Plexus means braided or entwined, from which is derived complexus meaning braided together, and the English word “complex” is derived from the Latin. Complexity is therefore associated with the intricate inter-twining or inter-connectivity of elements within a system and between a system and its environment.1 1.2 What are Complex Adaptive Systems? Many natural systems (e.g., brains, immune systems, ecologies, societies) and increasingly, many artificial systems (parallel and distributed computing systems, artificial intelligence systems, artificial neural networks, evolutionary programs) are characterized by apparently complex behaviors that emerge as a result of often nonlinear spatio-temporal interactions among a large number of component systems at different levels of organization.2 These systems have recently become known as Complex Adaptive 1 Eve Mitleton-Kelly, “Organisations as Co-evolving Complex Adaptive Systems,” British Academy of Management Conference, 1997. 2 Dr. Vasant Honavar, Complex Adaptive Systems Group at Iowa State University, http://www.cs.iastate.edu/~honavar/alife.isu.html, (date accessed: October 28, 2001).2 Systems (CAS). The theoretical framework is based on work in the natural sciences studying CAS, e.g., physics, chemistry, biology). The analysis of CAS is done by a combination of applied, theoretical and experimental methods (e.g., mathematics and computer simulation). CAS are dynamic systems able to adapt in and evolve with a changing environment. It is important to realize that there is no separation between a system and its environment in the idea that a system always adapts to a changing environment. Rather, the concept to be examined is that of a system closely linked with all other related systems making up an ecosystem. Within such a context, change needs to be seen in terms of co-evolution with all other related systems, rather than as adaptation to a separate and distinct environment. 2 History and Origins: Intellectual Figures The Santa Fe Institute (SFI) is a private, non-profit, multidisciplinary research and education center. Since its founding in 1984, SFI has devoted itself to creating a new kind of scientific research community, pursuing emerging science by providing multidisciplinary collaborations among visiting and residential scientists from the physical, biological, computational and social sciences. There are numerous scientists contributing to the field of complex adaptive systems. Due to time and space limitations, the following focuses on a few of the more well-known scientists and their contributing work. Murray Gell-Mann Murray Gell-Mann is Co-Chairman of the Science Board of the Santa Fe Institute and author of the popular science book The Quark and the Jaguar: Adventures in the Simple and the Complex. He was the Nobel laureate in physics in 1969 for his work on the theory of elementary particles. He currently focuses on complex adaptive systems. John Holland John Holland is the founder of the domain of genetic algorithms. Generic algorithms are parallel, computational representations of the processes of variation, recombination and selection on the basis of fitness that trigger most processes of evolution and adaptation. They have been successfully applied to general problem solving, control and optimization tasks, inductive learning (e.g., classifier systems), and the modeling of ecological systems (e.g., the ECHO model).3 Stuart Kauffman Stuart Kauffman is a biologist who has tried to understand how networks of mutually activating or inhibiting genes can give rise to the differentiation of organs and tissues during embryological development. His work has led him to investigate the properties of Boolean networks of different sizes and degrees of connectedness. He proposes that the self-organization displayed by such networks of genes or chemical reactions is a vital factor in evolution, corresponding to Darwinian selection by the environment. Ilya Prigogine Ilya Prigogine, a Nobel laureate chemistry in 1977 for his contributions to non-equilibrium thermodynamics, has studied the theory of dissipative structures. His work on dissipative structures have stimulated many scientists throughout the world and may have profound consequences for our understanding of biological systems. Prigogine aims for a better understanding of the role of time in the physical sciences and in biology. He has contributed significantly to the understanding of irreversible processes, particularly in systems far from equilibrium Brian Goodwin Brian Goodwin is a professor of biology in England and a member of the Board of Directors at the Santa Fe Institute. His work has been in ‘new’ biology – biology, in the form of an exact science, of complex