A Vectorial Approach to Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Azzali:2019:EuroGP,

• author = "Irene Azzali and Leonardo Vanneschi and Sara Silva and Illya Bakurov and Mario Giacobini",
• title = "A Vectorial Approach to Genetic Programming",
• booktitle = "EuroGP 2019: Proceedings of the 22nd European Conference on Genetic Programming",
• year = "2019",
• month = "24-26 " # apr,
• editor = "Lukas Sekanina and Ting Hu and Nuno Lourenco",
• series = "LNCS",
• volume = "11451",
• publisher = "Springer Verlag",
• address = "Leipzig, Germany",
• pages = "213--227",
• organisation = "EvoStar, Species",
• keywords = "genetic algorithms, genetic programming, Vector-based representation, Panel Data regression: Poster",
• isbn13 = "978-3-030-16669-4",
• URL = "https://hdl.handle.net/2318/1725688",
• URL = "https://iris.unito.it/retrieve/e27ce42f-33ca-2581-e053-d805fe0acbaa/Azzali.pdf",
• URL = "https://www.springer.com/us/book/9783030166694",
• DOI = "doi:10.1007/978-3-030-16670-0_14",
• size = "16 pages",
• abstract = "Among the various typologies of problems to which Genetic Programming (GP) has been applied since its origins, symbolic regression is one of the most popular. A common situation consists in the prediction of a target time series based on scalar features and other time series variables collected from multiple subjects. To manage this problem with GP data needs a panel representation where each observation corresponds to a collection on a subject at a precise time instant. However, representing data in this form may imply a loss of information: for instance, the algorithm may not be able to recognize observations belonging to the same subject and their recording order. To maintain the source of knowledge supplied by ordered sequences as time series, we propose a new approach to GP that keeps instances of the same observation together in a vector, introducing vectorial variables as terminals. This new representation allows aggregate functions in the primitive GP set, included with the purpose of describing the behaviour of vectorial variables. In this work, we perform a comparative analysis of vectorial GP (VE-GP) against standard GP (ST-GP). Experiments are conducted on different benchmark problems to highlight the advantages of this new approach.",
• notes = "http://www.evostar.org/2019/cfp_eurogp.php#abstracts Part of \cite{Sekanina:2019:GP} EuroGP'2019 held in conjunction with EvoCOP2019, EvoMusArt2019 and EvoApplications2019",

}

Genetic Programming entries for Irene Azzali Leonardo Vanneschi Sara Silva Illya Bakurov Mario Giacobini

Citations