Demonstrating Constraints to Diversity with a Tunably Difficulty Problem for Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{daida:2004:dctdwatdpfgp,

• title = "Demonstrating Constraints to Diversity with a Tunably Difficulty Problem for Genetic Programming",
• author = "Jason M. Daida and Michael E. Samples and Bryan T. Hart and Jeffry Halim and Aditya Kumar",
• pages = "1217--1224",
• booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary Computation",
• year = "2004",
• publisher = "IEEE Press",
• month = "20-23 " # jun,
• address = "Portland, Oregon",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Theoretical Foundations of Evolutionary Computation",
• URL = "http://sitemaker.umich.edu/daida/files/CEC04highlander.pdf",
• DOI = "doi:10.1109/CEC.2004.1331036",
• 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.",
• size = "8 pages",
• 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