Grammar-Based Immune Programming for Symbolic Regression

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@InProceedings{Bernardino:2009:ICARIS,

• author = "Heder S. Bernardino and Helio J. C. Barbosa",
• title = "Grammar-Based Immune Programming for Symbolic Regression",
• booktitle = "Proceedings of the 8th International Conference on Artificial Immune Systems (ICARIS)",
• year = "2009",
• editor = "Paul S. Andrews and Jon Timmis and Nick D. L. Owens and Uwe Aickelin and Emma Hart and Andrew Hone and Andy M. Tyrrell",
• volume = "5666",
• series = "Lecture Notes in Computer Science",
• pages = "274--287",
• address = "York, UK",
• month = aug # " 9-12",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, Artificial immune system, immune programming, symbolic regression",
• isbn13 = "978-3-642-03245-5",
• language = "English",
• URL = "http://dx.doi.org/10.1007/978-3-642-03246-2_26",
• DOI = "doi:10.1007/978-3-642-03246-2_26",
• abstract = "This paper presents a Grammar-based Immune Programming (GIP) that can evolve programs in an arbitrary language using a clonal selection algorithm. A context-free grammar that defines this language is used to decode candidate programs (antibodies) to a valid representation. The programs are represented by tree data structures as the majority of the program evolution algorithms do. The GIP is applied to symbolic regression problems and the results found show that it is competitive when compared with other algorithms from the literature.",

}

Genetic Programming entries for Heder Soares Bernardino Helio J C Barbosa

Citations