Continuous Hierarchical Fair Competition Model for Sustainable Innovation in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InCollection{Jianjun-Hu:2003:GPTP,
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author = "Jianjun Hu and Erik D. Goodman and Kisung Seo",
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title = "Continuous Hierarchical Fair Competition Model for
Sustainable Innovation in Genetic Programming",
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booktitle = "Genetic Programming Theory and Practice",
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publisher = "Kluwer",
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year = "2003",
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editor = "Rick L. Riolo and Bill Worzel",
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chapter = "6",
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pages = "81--98",
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keywords = "genetic algorithms, genetic programming, sustainable
innovation, HFC, fair competition principle",
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ISBN = "1-4020-7581-2",
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URL = "http://www.springer.com/computer/ai/book/978-1-4020-7581-0",
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DOI = "doi:10.1007/978-1-4419-8983-3_6",
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abstract = "Lack of sustainable search capability of genetic
programming has severely constrained its application to
more complex problems. A new evolutionary algorithm
model named the continuous hierarchical fair
competition (CHFC) model is proposed to improve the
capability of sustainable innovation for single
population genetic programming. It is devised by
extracting the fundamental principles underlying
sustainable biological and societal processes
originally proposed in the multi-population HFC model.
The hierarchical elitism, breeding probability
distribution and individual distribution control over
the whole fitness range enable CHFC to achieve
sustainable evolution while enjoying flexible control
of an evolutionary search process. Experimental results
demonstrate its capability to do robust sustainable
search and avoid the aging problem typical in genetic
programming.",
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notes = "Part of \cite{RioloWorzel:2003}",
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size = "pages",
- }
Genetic Programming entries for
Jianjun Hu
Erik Goodman
Kisung Seo
Citations