Open Access
Complex adaptive systems
Jason Brownlee
- 01 Jan 2007
TL;DR: The principles of complex adaptive systems as a framework are reviewed, providing a number of interpretations from eminent researches in the field, and the theory is used to phrase some ambiguus work in the fields of artificial immune systems and artificial life.
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Abstract: The field of Complex Adaptive Systems (CAS) is approximately 20 years old, having been established by physicists, economists, and others studying complexity at the Santa Fe Institute in New Mexico, USA. The field has spawned much work, such as Holland's contributions of genetic algorithms, classifier systems, and his ecosystem simulator, which assisted in provoking the fields of evolutionary computation and artificial life. The framework of inducted principles derived from many natural and artificial examples of complex systems has assisted in the investigation in such diverse fields of study as psychology, anthropology, genetic evolution, ecology, and business management theory, although a unified theory of such complex systems still appears to be a long way off. This work reviews the principles of complex adaptive systems as a framework, providing a number of interpretations from eminent researches in the field. Many example works are cited, and the theory is used to phrase some ambiguus work in the field of artificial immune systems and artificial life. The methodology of using simulations of CAS as the starting point for models in the field of biological inspired computation is postulated as an important contribution of CAS to that field.
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Adaptation in natural and artificial systems
John H. Holland
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TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
John H. Holland
- 01 May 1992
TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
16.6K
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The Origins of Order: Self-Organization and Selection in Evolution
Stuart A. Kauffman
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TL;DR: The structure of rugged fitness landscapes and the structure of adaptive landscapes underlying protein evolution, and the architecture of genetic regulatory circuits and its evolution.
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At Home in the Universe: The Search for the Laws of Self-Organization and Complexity
Stuart A. Kauffman
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Complexity: The Emerging Science at the Edge of Order and Chaos
M. Mitchell Waldrop
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