Balancing exploration and exploitation in genetic programming using inversion with individualized self-adaptation
Created by W.Langdon from
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- @Article{journals/ijhis/FitzgeraldR14,
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author = "Jeannie Fitzgerald and Conor Ryan",
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title = "Balancing exploration and exploitation in genetic
programming using inversion with individualized
self-adaptation",
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journal = "International Journal of Hybrid Intelligent Systems",
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year = "2014",
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number = "4",
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volume = "11",
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pages = "273--285",
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keywords = "genetic algorithms, genetic programming",
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bibdate = "2014-09-30",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/ijhis/ijhis11.html#FitzgeraldR14",
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URL = "http://content.iospress.com/download/international-journal-of-hybrid-intelligent-systems/his00199?id=international-journal-of-hybrid-intelligent-systems%2Fhis00199",
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URL = "http://dx.doi.org/10.3233/HIS-140199",
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DOI = "doi:10.3233/HIS-140199",
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size = "13 pages",
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abstract = "In this article we explore and develop a holistic
scheme of self adaptive, individualized genetic
operators combined with an adaptive tournament size
together with a novel implementation of an inversion
genetic operator which is suitable for tree based
Genetic Programming. We test this scheme on several
benchmark Binary Classification problems and find that
the proposed techniques deliver superior performance
when compared with both a tuned GP configuration and a
feedback adaptive Genetic Programming implementation.
Our results also demonstrate that an inversion operator
may have a useful role to play in exploitation,
particularly when used towards the end of evolution to
facilitate gradual convergence of the learning system
towards a good solution.",
- }
Genetic Programming entries for
Jeannie Fitzgerald
Conor Ryan
Citations