Arthur, W. B. (1999) Complexity and the Economy, Science, 284, Number 5411, pp. 107 - 109
Economics has been one of the first examples where a complex systems approach has been successfully applied to social sciences. Brian Arthur led the efforts in this area at the Santa Fe Institute and gives an overview of the main findings in this article.
Birbaumer, N., Lutzenberger, W., Rau, H., Mayer-Kress, G., Braun, C. (1996). Perception of Music and Dimensional Complexity of Brain Activity, International Journal of Bifurcations and Chaos, 6(2): 267-278
Nonlinear dimensional analysis of brain signals shows a resonant response to musical patterns that are chaotic. That confirms a hypothesis that elements of surprise within recognizable structures make a piece of music interesting.
Davis, L. (Ed.) (1991). The Genetic Algorithms Handbook, Van Nostrand Reinhold, New York
A compilation of representative methods and applications of genetic algorithms. The chapter by Forrest & Mayer-Kress studies models of international arms races and how evolutionary concepts can help to find solutions with high overall fitness.
Doheny-Farina, S. (1992). Rhetoric, Innovation, Technology: Case Studies of Technical Communication in Technology Transfers. Cambridge, Mass.: MIT Press.
Discusses the role of language and communication in the process of innovation.
Freeman, W.J. (1995). Societies of Brains, Lawrence Erlbaum Assoc. Inc, Hillsdale/NJ
Discusses what we can learn about human interactions within social groups from our knowledge about how the brain works.
Gates, B. (1999). Business @ The Speed Of Thought: Using A Digital Nervous System, Warner Books, New York
Concepts from problem solving in biological brains are applied to organization development and management. "Digital nervous systems" of business enterprises are one example of emergent structures within a global brain.
Haken, H. (1977). Synergetics: An Introduction: Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry, and Biology, Springer Verlag, Berlin
An introduction to self-organization and pattern formation from a physics perspective. Applications to innovations in social systems are discussed as applications of the general theory.
Holland, J. H. (1992). Adaptation In Natural And Artificial Systems: An Introductory Analysis With Applications To Biology, Control, And Artificial Intelligence, The MIT Press, Cambridge, MA
One of the inventors of genetic algorithms gives an introduction in the computational aspects of evolution in machine learning.
Kaufman, S. (1996). At Home in the Universe: The Search for Laws of Self-Organization and Complexity, Oxford University Press, Oxford
General exposition of a complex systems perspective on questions of self-organization with a focus on the origin of life.
Kelly, S., Allison, M.A. (1999). The Complexity Advantage: How the Science of Complexity Can Help Your Business Achieve Peak Performance, McGraw-Hill, New York
One of several books that have been published recently on the application of complex systems concepts to business management in general and to innovation in particular.
Mayer-Kress, G., Barczys, C. (1995). The Global Brain as an Emergent Structure from the Worldwide Computing Network, and its Implications for Modeling, The Information Society, Vol. 11, No 1, 1-28,
Cognitive events in the brain like those that lead to innovations are associated with the spontaneous formation of neuronal cell-assemblies. On the Internet virtual communication networks can be observed to form spontaneously in linked web pages. It is postulated that as a complex adaptive system the Internet will show the emergence of global network structures that are adapted to solve global problems.
Needham, J. (1956). Science and Civilization in China : History of Scientific Thought, Cambridge University Press
Comprehensive collection reviewing what is known about science and civilization in China. Needham tries to explain why scientific superiority that was held by China over Europe was reversed during the European Renaissance period.
Newell, K.M., Mayer-Kress, G., Liu, Y.T., (1999). Time Scales in Motor Learning and Development, Psychological Review, (to app.)
An overview of the role of time scales in understanding the theoretical basis of learning and development. The interpretation of innovations as bifurcations in complex, dynamical systems is based on results described in this paper.
Ray, T. S. (1991). Evolution and optimization of digital organisms. In: Billingsley K. R., E. Derohanes, H. Brown, III [eds.], Scientific Excellence in Supercomputing: The IBM 1990 Contest Prize Papers, The Baldwin Press, The University of Georgia, Pp. 489-531.
This is one of the first publications on "Tierra" an artificial life model that reproduces many features of natural evolution. A current more information about the model can be found at the web site http://www.hip.atr.co.jp/~ray/tierra/tierra.html
Smolin, L. (1997). The Life of the Cosmos, Oxford University Press
Uses ideas from complex systems to speculate about the existence of evolving universes outside our known universe. Presents a very large perspective of the concept of innovation and evolution.
Thom, R. (1989). Structural Stabiltiy and Morphogenesis, Paperback, Perseus Press
Describes the mathematical foundations of some of the basic mechanisms involved in pattern formation observed in complex systems. Elementary bifurcations are discussed in the framework of catastrophe theory.
Tornatzky, L. & Fleischer, M. (1990). The Processes of Technological Innovation, Lexington Books, New York
A more traditional approach to innovation in the more narrow sense of the word.
Wilson, E. O. (1998). Consilience: The Unity of Knowledge, Knopf, New York
Describes common aspects of gene-culture co-evolution. Illustrates the universal features of adaptation in complex systems.