Understanding grammatical evolution: initialisation

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{Nicolau:GPEM:initGE,

• author = "Miguel Nicolau",
• title = "Understanding grammatical evolution: initialisation",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2017",
• volume = "18",
• number = "4",
• pages = "467--507",
• month = dec,
• keywords = "genetic algorithms, genetic programming, Grammatical evolution Initialisation Representation bias Tree creation Symbolic regression Classification Design",
• ISSN = "1389-2576",
• URL = "https://link.springer.com/article/10.1007/s10710-017-9309-9",
• DOI = "doi:10.1007/s10710-017-9309-9",
• size = "41 pages",
• abstract = "Grammatical evolution is one of the most used variants of genetic programming, and ever since its introduction, several improvements have been suggested. One of these concerns the routine used to create the initial population. In this study, several proposed initialisation routines are compared; based on a detailed analysis of the generated initial populations, and subsequent results obtained on a large set of experiments, a variant of the PTC2 algorithm is shown to consistently outperform all other routines, while a variant of random initialisation provides a good compromise between efficiency and ease of implementation.",

}

Genetic Programming entries for Miguel Nicolau

Citations