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Conference Proceeding

GP vs GI: if you can't beat them, join them

Citation
Woodward J, Johnson C & Brownlee A (2016) GP vs GI: if you can't beat them, join them. In: Friedrich T (ed.) GECCO '16 Companion Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion. Genetic and Evolutionary Computation Conference, GECCO-2016, Denver, CO, USA, 20.07.2016-24.07.2016. New York: ACM, pp. 1155-1156. https://doi.org/10.1145/2908961.2931694

Abstract
Genetic Programming (GP) has been criticized for targeting irrelevant problems [12], and is also true of the wider machine learning community [11]. which has become detached from the source of the data it is using to drive the field forward. However, recently GI provides a fresh perspective on automated programming. In contrast to GP, GI begins with existing software, and therefore immediately has the aim of tackling real software. As evolution is the main approach to GI to manipulating programs, this connection with real software should persuade the GP community to confront the issues around what it originally set out to tackle i.e. evolving real software.

Keywords
Genetic Improvement (GI); Genetic Programming (GP)

StatusPublished
Author(s)Woodward, John; Johnson, Colin; Brownlee, Alexander
Publication date31/12/2016
Publication date online31/07/2016
URLhttp://hdl.handle.net/1893/23386
Related URLshttp://gecco-2016.sigevo.org/index.html/HomePage#&panel1-1
PublisherACM
Place of publicationNew York
ISBN978-1-4503-4323-7
ConferenceGenetic and Evolutionary Computation Conference, GECCO-2016
Conference locationDenver, CO, USA
Dates
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