Evolving Graphs with Cartesian Genetic Programming with Lexicase Selection
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{lavinas:2023:GGP,
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author = "Yuri Lavinas and Kevin Cortacero and
Sylvain Cussat-Blanc",
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title = "Evolving Graphs with Cartesian Genetic Programming
with Lexicase Selection",
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booktitle = "Graph-based Genetic Programming",
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year = "2023",
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editor = "Roman Kalkreuth and Thomas Baeck and
Dennis G. Wilson and Paul Kaufmann and Leo Francoso Dal Piccol Sotto and
Timothy Aktinson",
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pages = "1920--1924",
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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, cartesian
genetic programming, evolutionary computation,
graph-based methods, lexicase selection",
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isbn13 = "9798400701191",
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DOI = "doi:10.1145/3583133.3596402",
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size = "5 pages",
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abstract = "The automatic construction of an image filter is a
difficult task for which many recent machine-learning
methods have been proposed. Cartesian Genetic
Programming (CGP) has been effectively used in
image-processing tasks by evolving programs with a
function set specialized for computer vision. Although
standard CGP is able to construct understandable image
filter programs, we hypothesize that explicitly using a
mechanism to control the size of the generated filter
programs would help reduce the size of the final
solution while keeping comparable efficacy on a given
task. It is indeed central to keep the graph size as
contained as possible as it improves our ability to
understand them and explain their inner functioning. In
this work, we use the Lexicase selection as the
mechanism to control the size of the programs during
the evolutionary process, by allowing CGP to evolve
solutions based on performance and on the size of such
solutions. We extend Kartezio, a Cartesian Genetic
Programming for computer vision tasks, to generate our
programs. We found in our preliminary experiment that
CGP with Lexicase selection is able to achieve similar
performance to the standard CGP while keeping the size
of the solutions smaller.",
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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
Yuri Lavinas
Kevin Cortacero
Sylvain Cussat-Blanc
Citations