Introducing vectorized cluster crossover in Grammatical Evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{kowalczykiewicz:2024:GECCOcomp,
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author = "Michal Kowalczykiewicz and Piotr Lipinski",
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title = "Introducing vectorized cluster crossover in
Grammatical Evolution",
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booktitle = "Proceedings of the 2024 Genetic and Evolutionary
Computation Conference Companion",
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year = "2024",
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editor = "Ting Hu and Aniko Ekart",
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pages = "507--510",
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address = "Melbourne, Australia",
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series = "GECCO '24",
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month = "14-18 " # jul,
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organisation = "SIGEVO",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution, source code vector embeddings, latent vector
representations, code2vec: Poster",
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isbn13 = "979-8-4007-0495-6",
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DOI = "doi:10.1145/3638530.3654359",
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size = "4 pages",
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abstract = "This paper concerns machine learning approaches for
software engineering, in particular for discovering
hidden knowledge from data by learning latent vector
representations of source code, and incorporating it to
evolutionary algorithms evolving computer programs by
improving their crossover operators. It focuses on
Grammatical Evolution, as an example of an evolutionary
algorithm aiming at constructing a computer program,
and code2vec, as a technique of discovering an
efficient latent vector code representation. We propose
a code2vec-based crossover operator that outperformed
the regular one in computational experiments with a
number of benchmark computer programs.",
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notes = "GECCO-2024 GP A Recombination of the 33rd
International Conference on Genetic Algorithms (ICGA)
and the 29th Annual Genetic Programming Conference
(GP)",
- }
Genetic Programming entries for
Michal Kowalczykiewicz
Piotr Lipinski
Citations