Operator Choice and the Evolution of Robust Solutions

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InCollection{soule:2003:GPTP,

• author = "Terence Soule",
• title = "Operator Choice and the Evolution of Robust Solutions",
• booktitle = "Genetic Programming Theory and Practice",
• publisher = "Kluwer",
• year = "2003",
• editor = "Rick L. Riolo and Bill Worzel",
• chapter = "16",
• pages = "257--269",
• keywords = "genetic algorithms, genetic programming, Code growth, code bloat, operators, introns, design, robust solutions",
• ISBN = "1-4020-7581-2",
• URL = "http://www2.cs.uidaho.edu/~tsoule/research/chap16.pdf",
• URL = "http://www.springer.com/computer/ai/book/978-1-4020-7581-0",
• DOI = "doi:10.1007/978-1-4419-8983-3_16",
• abstract = "This research demonstrates that evolutionary pressure favouring robust solutions has a significant impact on the evolutionary process. More robust solutions are solutions that are less likely to be degraded by the genetic operators. This pressure for robust solutions can be used to explain a number of evolutionary behaviours. The experiments examine the effect of different types and rates of genetic operators on the evolution of robust solutions. Previously robustness was observed to occur through an increase in inoperative genes (introns). This work shows that alternative strategies to increase robustness can evolve. The results also show that different genetic operators lead to different strategies for improving robustness. These results can be useful in designing genetic operators to encourage particular evolutionary behaviors.",
• notes = "Part of \cite{RioloWorzel:2003}",

}

Genetic Programming entries for Terence Soule

Citations