Initialisation in Structured Grammatical Evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.7325
- @InProceedings{murphy:2023:GEWS2023,
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author = "Aidan Murphy and Nuno Lourenco and
Anthony Ventresque",
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title = "Initialisation in Structured Grammatical Evolution",
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booktitle = "Grammatical Evolution Workshop - 25 years of GE",
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year = "2023",
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editor = "Conor Ryan and Mahsa Mahdinejad and Aidan Murphy",
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pages = "2022--2028",
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address = "Lisbon, Portugal",
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series = "GECCO '23",
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month = "15-19 " # 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, initialisation, structured grammatical
evolution",
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isbn13 = "9798400701191",
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DOI = "
doi:10.1145/3583133.3596412",
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size = "7 pages",
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abstract = "Robust initialisation has shown to greatly improve the
performance of genetic programming on a wide variety of
tasks. Many of these have been adapted to work with
grammatical evolution, with varying success. We are the
first to examine the effectiveness of some of the most
popular grammatical evolution initialisation techniques
using structured grammatical evolution. Namely, we
investigate sensible initialisation and probabilistic
tree creation 2, as well as the standard initialisation
procedure used in structured grammatical evolution,
grow.We examine their performance, as well as the
diversity of solutions they create, on 7 well-known
benchmarks. We observe that probabilistic tree creation
2 created the fittest initialisation populations on
every benchmark considered. This did not result in
overall better runs, however, and SGE runs with below
average initialisation performance were seen to
overcome their {"}bad start{"}. The diversity of
solutions, particularly fitness diversity, at the end
of the run was lower for probabilistic tree creation 2
than for both sensible initialisation and grow.",
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notes = "GECCO-2023 A Recombination of the 32nd International
Conference on Genetic Algorithms (ICGA) and the 28th
Annual Genetic Programming Conference (GP)",
- }
Genetic Programming entries for
Aidan Murphy
Nuno Lourenco
Anthony Ventresque
Citations