Grammar-Based Immune Programming for Symbolic Regression
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Bernardino:2009:ICARIS,
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author = "Heder S. Bernardino and Helio J. C. Barbosa",
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title = "Grammar-Based Immune Programming for Symbolic
Regression",
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booktitle = "Proceedings of the 8th International Conference on
Artificial Immune Systems (ICARIS)",
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year = "2009",
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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",
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volume = "5666",
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series = "Lecture Notes in Computer Science",
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pages = "274--287",
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address = "York, UK",
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month = aug # " 9-12",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution, Artificial immune system, immune
programming, symbolic regression",
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isbn13 = "978-3-642-03245-5",
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language = "English",
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URL = "http://dx.doi.org/10.1007/978-3-642-03246-2_26",
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DOI = "doi:10.1007/978-3-642-03246-2_26",
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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