Balancing Parent and Offspring Selection in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{DBLP:conf/ausai/XieZ09,

• author = "Huayang Xie and Mengjie Zhang",
• title = "Balancing Parent and Offspring Selection in Genetic Programming",
• booktitle = "Proceedings of the 22nd Australasian Joint Conference on Artificial Intelligence (AI'09)",
• year = "2009",
• editor = "Ann E. Nicholson and Xiaodong Li",
• volume = "5866",
• series = "Lecture Notes in Computer Science",
• pages = "454--464",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• address = "Melbourne, Australia",
• month = dec # " 1-4",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-10438-1",
• DOI = "doi:10.1007/978-3-642-10439-8_46",
• abstract = "In order to drive Genetic Programming (GP) search towards an optimal situation, balancing selection pressure between the parent and offspring selection phases is an important aspect and very challenging. Our previous work showed that stochastic elements cannot be removed from both parent and offspring selections and suggested that maximising diversity in parents and minimising randomness in offspring could provide significantly good performance. This paper conducts additional carefully designed experiments to further investigate how diverse the parent should be if the offspring selection pressure is intensive. This paper shows that any attempt on adding more selection pressure to the parent selection can result in lower GP performance, and the higher the parent selection pressure, the worse the GP performance. The results confirm and strengthen the finding in our previous work.",

}

Genetic Programming entries for Huayang Jason Xie Mengjie Zhang

Citations