An Empirical Study on the Parametrization of Cartesian Genetic Programming
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- @InProceedings{Kaufmann:2017:GECCO,
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author = "Paul Kaufmann and Roman Kalkreuth",
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title = "An Empirical Study on the Parametrization of Cartesian
Genetic Programming",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference Companion",
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series = "GECCO '17",
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year = "2017",
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isbn13 = "978-1-4503-4939-0",
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address = "Berlin, Germany",
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pages = "231--232",
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size = "2 pages",
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URL = "http://doi.acm.org/10.1145/3067695.3075980",
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DOI = "doi:10.1145/3067695.3075980",
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acmid = "3075980",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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month = "15-19 " # jul,
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming",
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abstract = "Since its introduction two decades ago, the way
researchers parametrised and optimized Cartesian
Genetic Programming (CGP) remained almost unchanged. In
this work we investigate non-standard parametrisations
and optimization algorithms for CGP. We show that the
conventional way of using CGP, i.e. configuring it as a
single line optimized by an (1+4) Evolutionary
Strategies-style search scheme, is a very good choice
but that rectangular CGP geometries and more elaborate
metaheuristics, such as Simulated Annealing, can lead
to faster convergence rates.",
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notes = "Also known as \cite{Kaufmann:2017:ESP:3067695.3075980}
GECCO-2017 A Recombination of the 26th International
Conference on Genetic Algorithms (ICGA-2017) and the
22nd Annual Genetic Programming Conference (GP-2017)",
- }
Genetic Programming entries for
Paul Kaufmann
Roman Tobias Kalkreuth
Citations