The following text is from “Complexity and Complex Adaptive Systems.”

The common feature of all these process is that in each one a complex adaptive system acquires information about its environment and its own interaction with that environment, identifying regularities in that information, condensing those regularities into a kind of “schema” or model, and acting in the real world on the basis of that schema. In each case, there are various competing schema, and the results of the action in the real world feed back to influence the competition among these schema.

In the process of new information from the environment, the compressed schema unfolds to give prediction or behavior or both.

When the compression took place, regularities were abstracted from experience and compressed. The rest of experience, ascribable to change or to regularities too subtle to recognize, cannot be compressed and does not typically form part of the schema. When unfolding takes place, new material is adjoined, much of it again largely random, as “present data” or input from the real world.

Murray cited two examples of this process: one is biological evolution, the other is a scientific theory. At end of the article, he concludes:

Complex adaptive systems operate through the cycle of variable schemata, accidental circumstances, phenotypic consequences, and feedback of selection pressures to the competition among schemata. They explore a huge space of possibilities, with opening to higher level of complexity and to the generation of new types of complex adaptive systems.