Complex adaptive systems are special cases of complex systems. They are complex in that they are diverse and made up of multiple interconnected elements (and so a part of network science) and adaptive in that they have the capacity to change and learn from experience. The term complex adaptive systems (CAS) was coined at the interdisciplinary Santa Fe Institute (SFI), by John H. Holland, Murray Gell-Mann and others.

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The term complex adaptive systems, or complexity science, is often used to describe the loosely organized academic field that has grown up around the study of such systems. Complexity science is not a single theory— it encompasses more than one theoretical framework and is highly interdisciplinary, seeking the answers to some fundamental questions about living, adaptable, changeable systems.

Examples of complex adaptive systems include the stock market, social insect and ant colonies, the biosphere and the ecosystem, the brain and the immune system, the cell and the developing embryo, manufacturing businesses and any human social group-based endeavour in a cultural and social system such as political parties or communities. There are close relationships between the field of CAS and artificial life. In both areas the principles emergence and self-organization are very important.

[http://en.wikipedia.org/wiki/Complex_adaptive_system]