Combining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InCollection{Kaufmann:2017:miller,
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author = "Paul Kaufmann and Marco Platzner",
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title = "Combining Local and Global Search: A Multi-objective
Evolutionary Algorithm for Cartesian Genetic
Programming",
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booktitle = "Inspired by Nature: Essays Presented to Julian F.
Miller on the Occasion of his 60th Birthday",
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publisher = "Springer",
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year = "2017",
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editor = "Susan Stepney and Andrew Adamatzky",
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volume = "28",
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series = "Emergence, Complexity and Computation",
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chapter = "8",
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pages = "175--194",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming",
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isbn13 = "978-3-319-67996-9",
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DOI = "doi:10.1007/978-3-319-67997-6_8",
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abstract = "This work investigates the effects of the
periodization of local and global multi-objective
search algorithms. We rely on a model for periodization
and define a multi-objective evolutionary algorithm
adopting concepts from Evolutionary Strategies and
NSGAII. We show that our method excels for the
evolution of digital circuits on the Cartesian Genetic
Programming model as well as on some standard
benchmarks such as the ZDT6, especially when periodized
with standard multi-objective genetic algorithms.",
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notes = "part of \cite{miller60book}
https://link.springer.com/bookseries/10624",
- }
Genetic Programming entries for
Paul Kaufmann
Marco Platzner
Citations