- author = "James McDermott and David R. White and Sean Luke and Luca Manzoni and Mauro Castelli and Leonardo Vanneschi and Wojciech Jaskowski and Krzysztof Krawiec and Robin Harper and Kenneth {De Jong} and Una-May O'Reilly",
- title = "Genetic programming needs better benchmarks",
- booktitle = "GECCO '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference",
- year = "2012",
- editor = "Terry Soule and Anne Auger and Jason Moore and David Pelta and Christine Solnon and Mike Preuss and Alan Dorin and Yew-Soon Ong and Christian Blum and Dario Landa Silva and Frank Neumann and Tina Yu and Aniko Ekart and Will Browne and Tim Kovacs and Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and Giovanni Squillero and Nicolas Bredeche and Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and Martin Pelikan and Silja Meyer-Nienberg and Christian Igel and Greg Hornby and Rene Doursat and Steve Gustafson and Gustavo Olague and Shin Yoo and John Clark and Gabriela Ochoa and Gisele Pappa and Fernando Lobo and Daniel Tauritz and Jurgen Branke and Kalyanmoy Deb",
- isbn13 = "978-1-4503-1177-9",
- pages = "791--798",
- month = "7-11 " # jul,
- organisation = "SIGEVO",
- address = "Philadelphia, Pennsylvania, USA",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- note = "Winner GECCO 2022 ten year impact award",
- keywords = "genetic algorithms, genetic programming, Automatic programming, Program synthesis, Algorithms, Experimentation, Measurement, Benchmark",
-
URL = "
http://gpbenchmarks.org/wp-content/uploads/2019/08/paper1.pdf",
-
DOI = "
doi:10.1145/2330163.2330273",
- abstract = "Genetic programming (GP) is not a field noted for the rigour of its benchmarking. Some of its benchmark problems are popular purely through historical contingency, and they can be criticized as too easy or as providing misleading information concerning real-world performance, but they persist largely because of inertia and the lack of good alternatives. Even where the problems themselves are impeccable, comparisons between studies are made more difficult by the lack of standardization. We argue that the definition of standard benchmarks is an essential step in the maturation of the field. We make several contributions towards this goal. We motivate the development of a benchmark suite and define its goals; we survey existing practice; we enumerate many candidate benchmarks; we report progress on reference implementations; and we set out a concrete plan for gathering feedback from the GP community that would, if adopted, lead to a standard set of benchmarks.",
-
notes = "GP Benchmarks. See \cite{White:2013:GPEM}
Also known as \cite{2330273} GECCO-2012 A joint meeting of the twenty first international conference on genetic algorithms (ICGA-2012) and the seventeenth annual genetic programming conference (GP-2012)",
