I googled complex adaptive systems and got a university link with some Mac software:

http://cognitrn.psych.indiana.edu/rgoldsto/complex/

and a quote:

Students should gain both an intuitive appreciation for the behavior of complex adaptive systems as well as an understanding of their formal underpinnings.

An active exploration of complex systems is the only true way to come away with a practical understanding of them. In many cases, it is quite surprising to see the highly organized, orderly behavior that emerges from systems composed out "agents" behaving in accord with very simple rules. Many people who have worked with these computer simulations for an extended period of time have been struck by the qualitative increase in their knowledge, relative to simply seeing the equations underlying the systems or a verbal description.

Simulations should show how agents organize themselves dynamically, over space and time.

Students should be able to actively change the behavior of the systems by "tweaking" parameters. All of the simulations that I have written contain a substantial amount of flexibility in them. Students can feel in control of the simulation, and can discover new phenomena and interrelations by systematically changing parameters. Students can conduct experiments, and instantly see the results of the experiments. In addition, the interactivity makes the simulations more appealing to use, hopefully increasing the amount of time students will spend with them.

http://www.innovation.cc/volumes-issues/rogers-adaptivesystem7final.pdf

The Complex Adaptive Systems (CAS) Model was born of the scientific study of complexity. According to James Gleick, the inspiration for complexity science can be traced to John von Neumann’s dynamic weather system models of the 1950s at the Institute for Advanced Study in Princeton, New Jersey, an effort that, in turn, goes back to the work of the eighteenth-century philosopher-mathematician Laplace (Gleick, 1987, p. 14). The diffusion of innovationsmodel, credited to Everett Rogers, delineates the process by which an innovation spreads via certain communication channels among members of a social system (Rogers, 2003). Diffusion phenomena bear a resemblance to complex adaptive systems.

“In linear systems the relationship between cause and effect is smooth and proportionate. Linear systems respond to big changes in a big and proportionate manner and linear systems respond to small changes in an equally small and proportionate way” (Kiel, 1995). Most real life situations, on the other hand, are complex. Small changes in initial conditions, and later interventions of whatever size, can result in disproportionately large effects.

and from WIKI of course:

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

A CAS is a complex, self-similar collection of interacting adaptive agents. The study of CAS focuses on complex, emergent and macroscopic properties of the system. Various definitions have been offered by different researchers:

John H. Holland
A Complex Adaptive System (CAS) is a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents.[1]

Kevin Dooley
A CAS behaves/evolves according to three key principles: order is emergent as opposed to predetermined (c.f. Neural Networks), the system's history is irreversible, and the system's future is often unpredictable. The basic building blocks of the CAS are agents. Agents scan their environment and develop schema representing interpretive and action rules. These schema are subject to change and evolution.[2]

Other definitions
Macroscopic collections of simple (and typically nonlinearly) interacting units that are endowed with the ability to evolve and adapt to a changing environment.[3]