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Genetic programming needs better benchmarks

Genetic programming needs better benchmarks Genetic Programming Needs Better Benchmarks James McDermott — David R. White Sean Luke ¡ Luca Manzoni Mauro Castelli Leonardo Vanneschi¶ Wojciech Ja´ kowski s Krzysztof Krawiec Robin Harper — — Kenneth De Jong ¡ Una-May O ™Reilly — ABSTRACT Genetic programming (GP) is not a eld noted for the rigor 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 di ƒcult by the lack of standardization. We argue that the de nition of standard benchmarks is an essential step in the maturation of the eld. We make several contributions towards this goal. We motivate the development of a benchmark suite and de ne 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. Categories and Subject Descriptors I.2.2 [Arti http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

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Datasource
Association for Computing Machinery
Copyright
Copyright © 2012 by ACM Inc.
ISBN
978-1-4503-1177-9
doi
10.1145/2330163.2330273
Publisher site
See Article on Publisher Site

Abstract

Genetic Programming Needs Better Benchmarks James McDermott — David R. White Sean Luke ¡ Luca Manzoni Mauro Castelli Leonardo Vanneschi¶ Wojciech Ja´ kowski s Krzysztof Krawiec Robin Harper — — Kenneth De Jong ¡ Una-May O ™Reilly — ABSTRACT Genetic programming (GP) is not a eld noted for the rigor 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 di ƒcult by the lack of standardization. We argue that the de nition of standard benchmarks is an essential step in the maturation of the eld. We make several contributions towards this goal. We motivate the development of a benchmark suite and de ne 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. Categories and Subject Descriptors I.2.2 [Arti

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