Towards a dynamic benchmark for genetic programming

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

@InProceedings{Tuite:2013:GECCOcomp,

• author = "Cliodhna Tuite and Michael O'Neill and Anthony Brabazon",
• title = "Towards a dynamic benchmark for genetic programming",
• booktitle = "GECCO '13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion",
• year = "2013",
• editor = "Christian Blum and Enrique Alba and Thomas Bartz-Beielstein and Daniele Loiacono and Francisco Luna and Joern Mehnen and Gabriela Ochoa and Mike Preuss and Emilia Tantar and Leonardo Vanneschi and Kent McClymont and Ed Keedwell and Emma Hart and Kevin Sim and Steven Gustafson and Ekaterina Vladislavleva and Anne Auger and Bernd Bischl and Dimo Brockhoff and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Heike Trautmann and Muhammad Iqbal and Kamran Shafi and Ryan Urbanowicz and Stefan Wagner and Michael Affenzeller and David Walker and Richard Everson and Jonathan Fieldsend and Forrest Stonedahl and William Rand and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and Gisele L. Pappa and John Woodward and Jerry Swan and Krzysztof Krawiec and Alexandru-Adrian Tantar and Peter A. N. Bosman and Miguel Vega-Rodriguez and Jose M. Chaves-Gonzalez and David L. Gonzalez-Alvarez and Sergio Santander-Jimenez and Lee Spector and Maarten Keijzer and Kenneth Holladay and Tea Tusar and Boris Naujoks",
• isbn13 = "978-1-4503-1964-5",
• keywords = "genetic algorithms, genetic programming",
• pages = "151--152",
• month = "6-10 " # jul,
• organisation = "SIGEVO",
• address = "Amsterdam, The Netherlands",
• DOI = "doi:10.1145/2464576.2464649",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "Following a recent call for a suite of benchmarks for genetic programming, we investigate the criteria for a meaningful dynamic benchmark for GP. We explore the design of a dynamic benchmark for symbolic regression, based on semantic distance between evaluated functions, where larger distances serve as a proxy for greater environmental change. We do not find convincing evidence that lower semantic distance is a good proxy for greater ease in adapting to a change. We conclude that due to fundamental characteristics of GP, it is difficult to come up with a single dynamic benchmark problem which is generally applicable.",
• notes = "Also known as \cite{2464649} Distributed at GECCO-2013.",

}

Genetic Programming entries for Cliodhna Tuite Michael O'Neill Anthony Brabazon

Citations