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:1.8051

@InProceedings{Manfrini:2016:GECCOcomp,

• author = "Francisco A. L. Manfrini and Heder S. Bernardino and Helio J. C. Barbosa",
• title = "On Heuristics for Seeding the Initial Population of Cartesian Genetic Programming Applied to Combinational Logic Circuits",
• booktitle = "GECCO '16 Companion: Proceedings of the Companion Publication of the 2016 Annual Conference on Genetic and Evolutionary Computation",
• year = "2016",
• 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",
• pages = "105--106",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming: Poster",
• month = "20-24 " # jul,
• organisation = "SIGEVO",
• address = "Denver, USA",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• isbn13 = "978-1-4503-4323-7",
• DOI = "doi:10.1145/2908961.2909031",
• 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.",
• notes = "Distributed at GECCO-2016.",

}

Genetic Programming entries for Francisco Augusto Lima Manfrini Heder Soares Bernardino Helio J C Barbosa

Citations