On the Increase of Functional Information in Complex Systems

For complex systems of many interacting components, the functional information of a system is expected to increase if many different configurations of the system are subjected to selection for one or more functions according to a recently defined new law. A cellular automata model – a classic example of a complex system – was created as a testbench for this law, and the model’s evolutionary results were analyzed and documented by Functional Information theory. In the model, over 800,000 system configurations evolved and created 176 unique functional structures in a first phase of evolution, demonstrating the law’s validity. An additional discovery was made that correlates the functional information of a structure with the computational work in evolutionary generations required to create the structure. Sequential phases of evolution of the model build on the results of previous phases and reveal a growth in the complexity of created structures.