Elitism and aggregation methods in partial redundant evolutionary swarms solving a multi-objective tasks

Abstract

In evolutionary swarms adaptability and diversity are closely related concepts. In order to get a better understanding of their codependency we study a heterogeneous evolutionary multi-agent system with different rates of redundancy within the genetic material. The agents process a dynamic multi-objective task, where their genetic material defines their efficiency concerning the different objective functions of that task. One focus of this study is the influence of an elitist behavior performed by the agents during the evolutionary process, where an agent can decline the genetic material of another agent if it does not meet specific requirements. Further we analyze the impact of three different methods to aggregate the objective values into a single fitness value that is applicable for the evolutionary mechanism of the system. The results show that heterogeneity in the optimization behavior of the agents is very beneficial as it maintains a higher diversity in the system. The elitist behavior of the agents slows the evolutionary process but gives it a stronger pull towards qualitatively higher positions in the objective space. Indeed, the pace of the evolutionary process ultimately has a higher impact on the adaptability of the system than the amount of redundancy in the genetic information.