An Evolutionary Approach to Complex System Regulation Using Grammatical Evolution
Saoirse Amarteifio, Michael O’Neill · The MIT Press eBooks · 2004
Motivated by difficulties in engineering adaptive distributed systems, we consider a method to evolve cooperation in swarms to model dynamical systems. We consider an in-formation processing swarm model that we find to be use-ful in studying control methods for adaptive distributed sys-tems and attempt to evolve systems that form consistent pat-terns through the interaction of constituent agents or parti-cles. This model considers artificial ants as walking sensors in an information-rich environment. Grammatical Evolution is combined with this swarming model as we evolve an ant’s response to information. The fitness of the swarm depends on information processing by individual ants, which should lead to appropriate macroscopic spatial and/or temporal patterns. We discuss three primary issues, which are tractability, rep-resentation and fitness evaluation of dynamical systems and show how Grammatical Evolution supports a promising ap-proach to addressing these concerns.