For more information contact Luis Rocha at rocha@indiana.edu.
Last Modified: May 25, 2005
Citation: Huang, Chien-feng and Luis M. Rocha. [2005]. "Tracking Extrema in Dynamic Environments using a Coevolutionary Agent-based Model of Genotype Edition". In: Genetic and Evolutionary Computation Conference: GECCO 2005. ACM Press, pp. 545-552.
The full paper is available in Adobe Acrobat (.pdf) format only. Due to mathematical notation and graphics, only the abstract is presented here.
Abstract.
Typical applications of evolutionary optimization in static environments involve the approximation of the extrema of functions. For dynamic environments, the interest is not to locate the extrema but to follow it as closely as possible. This paper compares the extrema-tracking performance of a traditional Genetic Algorithm and a coevolutionary agent- based model of Genotype Editing (ABMGE). This model is constructed using several genetic editing characteristics that are gleaned from the RNA editing system as observed in several organisms. The incorporation of editing mech- anisms provides a means for arti¯cial agents with genetic descriptions to gain greater phenotypic plasticity. By allow- ing the family of editors and the genotypes of agents to co- evolve using the re-generation of editors as a control switch for environmental changes, the arti¯cial agents in ABMGE can discover proper editors to facilitate the tracking of the extrema in dynamic environments. We will show that this agent-based model, together with a coevolutionary mecha- nism, is more adaptive and robust than the GA. We expect the framework proposed in this paper to advance the current state of research of Evolutionary Computation in dynamic environments.
