- author = "Ibrahim Kuscu",
- title = "Generalisation and Domain Specific Functions in Genetic Programming",
- booktitle = "Proceedings of the 2000 Congress on Evolutionary Computation CEC00",
- year = "2000",
- pages = "1393--1400",
- volume = "2",
- address = "La Jolla Marriott Hotel La Jolla, California, USA",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "6-9 " # jul,
- organisation = "IEEE Neural Network Council (NNC), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, Monk-2 problem, domain specific functions, experiments, generalisation, incomplete data sets, learning bias, parity problems, relational learning problems, generalisation (artificial intelligence), learning (artificial intelligence), learning systems",
- ISBN = "0-7803-6375-2",
- broken = "http://www.iuj.ac.jp/faculty/ik/pubs/cec2000.pdf",
-
URL = "
http://citeseer.ist.psu.edu/502977.html",
-
DOI = "
doi:10.1109/CEC.2000.870815",
- size = "8 pages",
- abstract = "This research presents an evaluation of user defined domain specific functions of genetic programming using relational learning problems, generalisation for this class of learning problems and learning bias. After providing a brief theoretical background, two sets of experiments are detailed: experiments and results concerning the Monk-2 problem and experiments attempting to evolve generalising solutions to parity problems with incomplete data sets. The results suggest that using nonproblem specific functions may result in greater generalisation for relational problems.",
-
notes = "CEC-2000 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.
IEEE Catalog Number = 00TH8512,
Library of Congress Number = 00-018644",
