%0 Report %1 Kuscu:1995:elrst1 %A Kuscu, Ibrahim %C Falmer, Brighton, Sussex, UK %D 1995 %K algorithms, genetic programming %N 394 %T Evolution of learning rules for supervised tasks I: simple learning problems %U ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp394.ps.Z %X 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.

@techreport{Kuscu:1995:elrst1, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Falmer, Brighton, Sussex, UK}, author = {Kuscu, Ibrahim}, biburl = {https://www.bibsonomy.org/bibtex/24583e0140ff1dd04aceff47ac8fbd79f/brazovayeye}, institution = {School of Cognitive and Computing Sciences, University of Sussex}, interhash = {bbd974ec2437e0f07c67e89b93a1bc50}, intrahash = {4583e0140ff1dd04aceff47ac8fbd79f}, keywords = {algorithms, genetic programming}, month = {10 November}, number = 394, size = {18 pages}, timestamp = {2008-06-19T17:44:33.000+0200}, title = {Evolution of learning rules for supervised tasks {I}: simple learning problems}, type = {Cognitive Science Research Paper}, url = {ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp394.ps.Z}, year = 1995 }