Controlling complexity

Abstract

Complex systems and dynamics are present in many parts of daily life and branches of science. This participation is continuation of our previous research, that introduced a novelty method of visualization and possible control of complex networks, that are used to visualize dynamics of evolutionary algorithms. Selected evolutionary algorithms are used as an example in order to show how its behavior can be understood as complex network and controlled via conversion into CML system - a model based on mutually joined nonlinear n equations. The main aim of this investigation was to show that dynamics of evolutionary algorithms can be converted to CML system and then controlled. Selected results of evolutionary controlled CML system are discussed here. © 2012 American Institute of Physics.