Evolution of learning rules for supervised tasks I: simple learning problems

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@TechReport{Kuscu:1995:elrst1,

• author = "Ibrahim Kuscu",
• title = "Evolution of learning rules for supervised tasks I: simple learning problems",
• institution = "School of Cognitive and Computing Sciences, University of Sussex",
• year = "1995",
• type = "Cognitive Science Research Paper",
• number = "394",
• address = "Falmer, Brighton, Sussex, UK",
• month = "10 " # nov,
• keywords = "genetic algorithms, genetic programming",
• URL = "ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp394.ps.Z",
• abstract = "Initial experiments with a genetic-based encoding schema are presented as a potentially powerful tool to discover learning rules by means of evolution. Several simple supervised learning tasks are tested. The results indicate the potential of the encoding schema to discover learning rules for more complex and larger learning problems.",
• size = "18 pages",

}

Genetic Programming entries for Ibrahim Kuscu

Citations