Diversity analysis in cellular and multipopulation genetic programming

This paper presents a study that evaluates the influence of the parallel genetic programming (GP) models in maintaining diversity in a population. The parallel models used are the cellular and the multipopulation one. Several measures of diversity are considered to gain a deeper understanding of the conditions under which the evolution of both models is successful. Three standard test problems are used to illustrate the different diversity measures and analyze their correlation with performance. Results show that diversity is not necessarily synonym of good convergence.

• Type: Conference
• Year: 2003
• Where: CEC
• Authors: Gianluigi Folino, Clara Pizzuti, Giandomenico Spezzano, Leonardo Vanneschi, Marco Tomassini
• Keywords: Artificial Intelligence, CEC 2003, Parallel Genetic Programming, Parallel Models, Several Measures