The Generalisation Ability of a Selection Architecture for Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Jackson:2008:PPSN,
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author = "David Jackson",
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title = "The Generalisation Ability of a Selection Architecture
for Genetic Programming",
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booktitle = "Parallel Problem Solving from Nature - PPSN X",
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year = "2008",
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editor = "Gunter Rudolph and Thomas Jansen and Simon Lucas and
Carlo Poloni and Nicola Beume",
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volume = "5199",
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series = "LNCS",
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pages = "468--477",
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address = "Dortmund",
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month = "13-17 " # sep,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-87699-5",
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DOI = "doi:10.1007/978-3-540-87700-4_47",
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abstract = "As an alternative to various existing approaches to
incorporating modular decomposition and reuse in
genetic programming (GP), we have proposed a new method
for hierarchical evolution. Based on a division of the
problem's test case inputs into subsets, it employs a
program structure that we refer to as a selection
architecture. Although the performance of GP systems
based on this architecture has been shown to be
superior to that of conventional systems, the nature of
evolved programs is radically different, leading to
speculation as to how well such programs may generalise
to deal with previously unseen inputs. We have
therefore performed additional experimentation to
evaluate the approach's generalisation ability, and
have found that it seems to stand up well against
standard GP in this regard.",
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notes = "PPSN X",
- }
Genetic Programming entries for
David Jackson
Citations