Kenneth De Jong

To successfully apply evolutionary algorithms to the solution of increasingly complex problems, we must develop effective techniques for evolving solutions in the form of interacting coadapted subcomponents. One of the major difficulties is finding computational extensions to our current evolutionary paradigms that will enable such subcomponents to "emerge" rather than being hand designed. In this paper, we describe an architecture for evolving such subcomponents as a collection of cooperating species. Given a simple string-matching task, we show that evolutionary pressure to increase the overall fitness of the ecosystem can provide the needed stimulus for the emergence of an appropriate number of interdependent subcomponents that cover multiple niches, evolve to an appropriate level of generality, and adapt as the number and roles of their fellow subcomponents change over time. We then explore these issues within the context of a more complicated domain through a case study involving the evolution of artificial neural networks.

Article Share on Evolutionary computation: a unified approach Author: Kenneth De Jong George Mason University, Fairfax, VA George Mason University, Fairfax, VAView Profile Authors Info & Claims GECCO '07: Proceedings of the 9th annual conference companion on Genetic and evolutionary computationJuly 2007 Pages 3158–3171https://doi.org/10.1145/1274000.1274109Published:07 July 2007Publication History 72citation361DownloadsMetricsTotal Citations72Total Downloads361Last 12 Months4Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access