Promoting Phenotypic Diversity in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Jackson:2010:PPSN,
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author = "David Jackson",
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title = "Promoting Phenotypic Diversity in Genetic
Programming",
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booktitle = "PPSN 2010 11th International Conference on Parallel
Problem Solving From Nature",
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year = "2010",
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editor = "Robert Schaefer and Carlos Cotta and
Joanna Kolodziej and Guenter Rudolph",
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publisher = "Springer",
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pages = "472--481",
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series = "Lecture Notes in Computer Science",
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address = "Krakow, Poland",
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month = "11-15 " # sep,
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volume = "6239",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1007/978-3-642-15871-1_48",
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abstract = "Population diversity is generally seen as playing a
crucial role in the ability of evolutionary computation
techniques to discover solutions. In genetic
programming, diversity metrics are usually based on
structural properties of individual program trees, but
are also sometimes based on the spread of fitness
values in the population. We explore the use of a
further interpretation of diversity, in which
differences are measured in terms of the behaviour of
programs when executed. Although earlier work has shown
that improving behavioural diversity in initial GP
populations can have a marked beneficial effect on
performance, further analysis reveals that lack of
behavioural diversity is a problem throughout whole
runs, even when other diversity levels are high. To
address this, we enhance phenotypic diversity via
modifications to the crossover operator, and show that
this can lead to additional performance improvements.",
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affiliation = "Dept. of Computer Science, University of Liverpool,
Liverpool, L69 3BX United Kingdom",
- }
Genetic Programming entries for
David Jackson
Citations