Demonstrating Constraints to Diversity with a Tunably Difficulty Problem for Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8178
- @InProceedings{daida:2004:dctdwatdpfgp,
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title = "Demonstrating Constraints to Diversity with a Tunably
Difficulty Problem for Genetic Programming",
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author = "Jason M. Daida and Michael E. Samples and
Bryan T. Hart and Jeffry Halim and Aditya Kumar",
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pages = "1217--1224",
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booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary
Computation",
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year = "2004",
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publisher = "IEEE Press",
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month = "20-23 " # jun,
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address = "Portland, Oregon",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Theoretical
Foundations of Evolutionary Computation",
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URL = "http://sitemaker.umich.edu/daida/files/CEC04highlander.pdf",
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DOI = "doi:10.1109/CEC.2004.1331036",
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abstract = "This paper introduces a tunably difficult problem for
genetic programming (GP) that probes for an upper bound
to the amount of heterogeneity that can be represented
by a single individual. Although GP's variable-length
representation would suggest that there is no upper
bound, our results indicate otherwise. The results
provide insight into the dynamics that occur during the
course of a GP run.",
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size = "8 pages",
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notes = "CEC 2004 - A joint meeting of the IEEE, the EPS, and
the IEE.",
- }
Genetic Programming entries for
Jason M Daida
Michael E Samples
Bryan Hart
Jeffry Halim
Aditya Kumar
Citations