Assessing Hierarchical Cooperative CoEvolution

Recently, many research efforts are directed towards coevolutionary algorithms. The present work aims at the assessment of Hierarchical Cooperative CoEvolution (HCCE) being properly formulated to address hierarchical problems where simple components having separate design objectives, are parts of other more complex ones. HCCE is able to highlight the specialties of each component and additionally enforce their successful integration in a composite structure. Here we present HCCE describing also the internal dynamics that provide its effectiveness in addressing difficult distributed design problems. Additionally, the results described in the present work attest to its validity and superior performance against ordinary Unimodal evolution, and Enforced SubPopulation coevolution.

• Type: Conference
• Year: 2007
• Where: ICTAI
• Authors: Michail Maniadakis, Panos E. Trahanias
• Keywords: Artificial Intelligence, Hierarchical Cooperative CoEvolution, ICTAI 2007, Present Work, Present Work Attest