Complexity engineering, evolution and optimality of structures

Abstract

Complexity Engineering deals with harnessing the power of Cellular Automata (CA) like simple models to solve real life difficult and complex engineering problems, dealing with systems that have very simple components that collectively exhibit complex behaviors. The state transition rules are generally fixed in a CA, but evolution of the rules, is considered here. To evolve the local rules, we use the Genetic Algorithm (GA) model. The example application described here will serve to demonstrate that the GAs can discover CA rules that give rise to emergent computational strategies by self-organization and exhibit globally coordinated tasks for optimization, with simple local interactions only.