Promoting Phenotypic Diversity in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Jackson:2010:PPSN,

• author = "David Jackson",
• title = "Promoting Phenotypic Diversity in Genetic Programming",
• booktitle = "PPSN 2010 11th International Conference on Parallel Problem Solving From Nature",
• year = "2010",
• editor = "Robert Schaefer and Carlos Cotta and Joanna Kolodziej and Guenter Rudolph",
• publisher = "Springer",
• pages = "472--481",
• series = "Lecture Notes in Computer Science",
• address = "Krakow, Poland",
• month = "11-15 " # sep,
• volume = "6239",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1007/978-3-642-15871-1_48",
• abstract = "Population diversity is generally seen as playing a crucial role in the ability of evolutionary computation techniques to discover solutions. In genetic programming, diversity metrics are usually based on structural properties of individual program trees, but are also sometimes based on the spread of fitness values in the population. We explore the use of a further interpretation of diversity, in which differences are measured in terms of the behaviour of programs when executed. Although earlier work has shown that improving behavioural diversity in initial GP populations can have a marked beneficial effect on performance, further analysis reveals that lack of behavioural diversity is a problem throughout whole runs, even when other diversity levels are high. To address this, we enhance phenotypic diversity via modifications to the crossover operator, and show that this can lead to additional performance improvements.",
• affiliation = "Dept. of Computer Science, University of Liverpool, Liverpool, L69 3BX United Kingdom",

}

Genetic Programming entries for David Jackson

Citations