Artificial Immune System Programming for Symbolic Regression

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{johnson03,

• author = "Colin G. Johnson",
• title = "Artificial Immune System Programming for Symbolic Regression",
• booktitle = "Genetic Programming, Proceedings of EuroGP'2003",
• year = "2003",
• editor = "Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa",
• volume = "2610",
• series = "LNCS",
• pages = "345--353",
• address = "Essex",
• publisher_address = "Berlin",
• month = "14-16 " # apr,
• organisation = "EvoNet",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming: Poster",
• ISBN = "3-540-00971-X",
• URL = "http://link.springer.com/chapter/10.1007/3-540-36599-0_32",
• DOI = "doi:10.1007/3-540-36599-0_32",
• abstract = "Artificial Immune Systems are computational algorithms which take their inspiration from the way in which natural immune systems learn to respond to attacks on an organism. This paper discusses how such a system can be used as an alternative to genetic algorithms as a way of exploring program-space in a system similar to genetic programming. Some experimental results are given for a symbolic regression problem. The paper ends with a discussion of future directions for the use of artificial immune systems in program induction.",
• notes = "EuroGP'2003 held in conjunction with EvoWorkshops 2003",

}

Genetic Programming entries for Colin G Johnson

Citations