Random Generator Quality and GP Performance
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{meysenburg:1999:RGQGP,
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author = "Mark M. Meysenburg and James A. Foster",
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title = "Random Generator Quality and GP Performance",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference",
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year = "1999",
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editor = "Wolfgang Banzhaf and Jason Daida and
Agoston E. Eiben and Max H. Garzon and Vasant Honavar and
Mark Jakiela and Robert E. Smith",
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volume = "2",
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pages = "1121--1126",
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address = "Orlando, Florida, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "13-17 " # jul,
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publisher = "Morgan Kaufmann",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-55860-611-4",
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URL = "http://citeseer.ist.psu.edu/471279.html",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco1999/GP-416.pdf",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco1999/GP-416.ps",
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abstract = "In previous studies, the authors found that
pseudo-random number generator (PRNG) quality had
little effect on the performance of a simple genetic
algorithm (GA). This paper extends our work to the area
of genetic programming (GP). We examine the effect of
PRNG quality on the performance of GP techniques. We
detail a set of PRNGs which generate random numbers
through various techniques, and a method for evaluating
the quality of these PRNGs. We explain the application
of detailed statistical analysis to the results of many
individual GP runs, over a set of four GP test
problems. We found no evidence to support the notion
that higher quality PRNGs caused improved GP
performance.",
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notes = "GECCO-99 A joint meeting of the eighth international
conference on genetic algorithms (ICGA-99) and the
fourth annual genetic programming conference (GP-99)",
- }
Genetic Programming entries for
Mark M Meysenburg
James A Foster
Citations