Machine Learning with Genetic Programming: Some Challenges

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Unpublished{McKay:2003:apsies,

• author = "R. I. (Bob) McKay",
• howpublished = "Asia-Pacific Symposium on Intelligent and Evolutionary Systems",
• address = "Kitakyushu, Japan",
• month = nov,
• note = "Keynote Address",
• title = "Machine Learning with Genetic Programming: Some Challenges",
• URL = "http://sc.snu.ac.kr/PAPERS/aj03.pdf",
• year = "2003",
• keywords = "genetic algorithms, genetic programming, Search Bias, Hierarchical, Developmental, Genotype-Phenotype mapping",
• size = "6 pages",
• abstract = "Genetic Programming has achieved a great deal in the twenty or so years since its inception. Nevertheless, there remain a wide range of challenges and open questions: what form do the building blocks of good programs take; how may they be identified and promoted? Particularly in the light of Daida's work on the structural restrictions of GP, there are critical questions on the appropriate representations for GP, and the possibility of non-traditional genetic operators. Finally, it is clear that the operation of GP systems still differs in important ways from that of biological systems, so there is opportunity for further inspiration from biological systems.",

}

Genetic Programming entries for R I (Bob) McKay

Citations