A quantitative analysis of the simplification genetic operator

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

@InProceedings{Zhan:2014:GECCOcomp,

• author = "Haoxi Zhan",
• title = "A quantitative analysis of the simplification genetic operator",
• booktitle = "GECCO 2014 student workshop",
• year = "2014",
• editor = "Tea Tusar and Boris Naujoks",
• isbn13 = "978-1-4503-2881-4",
• keywords = "genetic algorithms, genetic programming",
• pages = "1077--1080",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Vancouver, BC, Canada",
• URL = "http://doi.acm.org/10.1145/2598394.2605684",
• DOI = "doi:10.1145/2598394.2605684",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "The simplification function was introduced to PushGP as a tool to reduce the sizes of evolved programs in final reports. While previous work suggests that simplification could reduce the sizes significantly, nothing has been done to study its impacts on the evolution of Push programs. In this paper, we show the impact of simplification as a genetic operator. By conducting test runs on the U.S. change problem, we show that using simplification operator with PushGP, lexicase selection and ULTRA could increase the possibility to find solutions in the short term while it might remove some useful genetic materials for the long term.",
• notes = "Clojush Also known as \cite{2605684} Distributed at GECCO-2014.",

}

Genetic Programming entries for Haoxi Zhan

Citations