Facilitating Function Application in Code Building Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{helmuth:2024:GECCO,
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author = "Thomas Helmuth and Jayden Fedoroff and
Edward Pantridge and Lee Spector",
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title = "Facilitating Function Application in Code Building
Genetic Programming",
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booktitle = "Proceedings of the 2024 Genetic and Evolutionary
Computation Conference",
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year = "2024",
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editor = "Ting Hu and Aniko Ekart and Julia Handl and
Xiaodong Li and Markus Wagner and Mario Garza-Fabre and
Kate Smith-Miles and Richard Allmendinger and Ying Bi and
Grant Dick and Amir H Gandomi and
Marcella Scoczynski Ribeiro Martins and Hirad Assimi and
Nadarajen Veerapen and Yuan Sun and Mario Andres Munyoz and
Ahmed Kheiri and Nguyen Su and Dhananjay Thiruvady and Andy Song and
Frank Neumann and Carla Silva",
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pages = "887--895",
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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, automatic
programming, inductive program synthesis, function
application",
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isbn13 = "979-8-4007-0494-9",
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DOI = "doi:10.1145/3638529.3654068",
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size = "9 pages",
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abstract = "Code Building Genetic Programming (CBGP) is a method
for general inductive program synthesis that uses a
genetic algorithm and a formal type system to evolve
linear genomes that are compiled into type-safe
programs in a host language. Prior work showed that
CBGP can evolve programs that use arbitrary
abstractions from existing codebases along with
higher-order functions and polymorphism. In tests on
benchmark problems, however, the problem solving
capabilities of CBGP have been mixed. One hypothesized
explanation for weak performance on some problems is
that many functions encountered during the compilation
process are typically not applied. Here we propose two
modifications to the compilation algorithm, both of
which make it more likely that functions will be
applied when composing programs. The first modification
changes how frequently CBGP attempts to perform
function application, while the second allows the
construction of function applications to backtrack.
While both modifications increase solution rates on
benchmark problems, the backtracking modification shows
more promise with a modest increase in computational
cost and no additional configuration requirements. We
argue that this modification should be considered the
new standard compilation algorithm for CBGP systems.",
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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
Thomas Helmuth
Jayden Fedoroff
Edward R Pantridge
Lee Spector
Citations