On Heuristics for Seeding the Initial Population of Cartesian Genetic Programming Applied to Combinational Logic Circuits
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Manfrini:2016:GECCOcomp,
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author = "Francisco A. L. Manfrini and Heder S. Bernardino and
Helio J. C. Barbosa",
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title = "On Heuristics for Seeding the Initial Population of
Cartesian Genetic Programming Applied to Combinational
Logic Circuits",
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booktitle = "GECCO '16 Companion: Proceedings of the Companion
Publication of the 2016 Annual Conference on Genetic
and Evolutionary Computation",
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year = "2016",
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editor = "Tobias Friedrich and Frank Neumann and
Andrew M. Sutton and Martin Middendorf and Xiaodong Li and
Emma Hart and Mengjie Zhang and Youhei Akimoto and
Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and
Daniele Loiacono and Julian Togelius and
Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and
Faustino Gomez and Carlos M. Fonseca and
Heike Trautmann and Alberto Moraglio and William F. Punch and
Krzysztof Krawiec and Zdenek Vasicek and
Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and
Boris Naujoks and Enrique Alba and Gabriela Ochoa and
Simon Poulding and Dirk Sudholt and Timo Koetzing",
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pages = "105--106",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming: Poster",
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month = "20-24 " # jul,
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organisation = "SIGEVO",
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address = "Denver, USA",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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isbn13 = "978-1-4503-4323-7",
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DOI = "doi:10.1145/2908961.2909031",
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abstract = "The design of circuits is an important research field
and the corresponding optimization problems are complex
and computationally expensive. Here, a Cartesian
Genetic Programming (CGP) technique was used to design
combinational logic circuits. Several configurations
were tested for seeding the initial population. First,
the number of rows, columns, and levels-back were
varied. In addition, the initial population was
generated using only NAND gates. These configurations
were compared with results from the literature in four
benchmark circuits, where in all instances it was
possible to find that some seeding configurations
contributed beneficially to the evolutionary process,
allowing CGP to find a solution employing a lower
number of fitness evaluations. Finally, the variation
of the number of nodes of the individuals during the
search was also analysed and the results showed that
there is a correlation between the topology of the
initial population and the region of the search space
which is explored.",
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notes = "Distributed at GECCO-2016.",
- }
Genetic Programming entries for
Francisco Augusto Lima Manfrini
Heder Soares Bernardino
Helio J C Barbosa
Citations