University of Cincinnati


Last updated on November 3, 2010

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Complex adaptive systems (CAS) are all around us --- in the natural world as well as in engineered environments. Examples include traffic and communication networks, human organizations, markets, economies, cities, insect colonies, ecosystems, the nervous and immune ystems, living organisms, and life itself.

The research conducted in the Complex Adaptive Systems Lab has two purposes:

The notion that complex adaptive systems can be studied as a class is based on the assumption that the same fundamental principles underlie all complex systems, ranging from neurosciene to economics, molecular biology to traffic engineering, ecology to the internet. The discovery and application of these principles is the goal of complex systems research.

Some of the fundamental attributes that characterize complex adaptive systems and distinguish them from systems that are merely "complicated" --- such as jet engines or computers --- are the following:

The distributed, self-organized and multi-scale nature of complex systems makes them extremely scalable, robust, and flexible. These attributes allow them to survive, grow and evolve in changing environments without need for explicit repair or redesign. Since structure and process at large scales emerge spontaneously from small-scale interactions, there is no centralized control and no need to explicitly determine the state of the entire system. This avoids the combinatorial explosion seen in centrally controlled large-scale systems, and makes complex adaptive systems extremely scalable.