- author = "Tina Yu",
- title = "Structure Abstraction and Genetic Programming",
- booktitle = "Proceedings of the Congress on Evolutionary Computation",
- year = "1999",
- editor = "Peter J. Angeline and Zbyszek Michalewicz and Marc Schoenauer and Xin Yao and Ali Zalzala",
- volume = "1",
- pages = "652--659",
- address = "Mayflower Hotel, Washington D.C., USA",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "6-9 " # jul,
- organisation = "Congress on Evolutionary Computation, IEEE / Neural Networks Council, Evolutionary Programming Society, Galesia, IEE",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, theory, general even parity problem, perfect solutions, program representation selection, program structures, search space, structure abstraction, evolutionary computation, search problems",
- ISBN = "0-7803-5536-9 (softbound)",
- ISBN = "0-7803-5537-7 (Microfiche)",
-
URL = "
http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/cec99.pdf",
-
DOI = "
doi:10.1109/CEC.1999.781995",
- abstract = "The selection of program representation can have strong impact on the performance of genetic programming. Previous work has shown that a particular program representation which supports structure abstraction is very effective in solving the general even parity problem. We investigate program structures and analyse all perfect solutions in the search space to provide explanation of why structure abstraction is so effective with this problem. This work provides guidelines for the application of structure abstraction to other problems",
-
notes = "CEC-99 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.
Library of Congress Number = 99-61143
",
