- author = "Robert McKay and Hussein Abbass",
- title = "Anticorrelation Measures in Genetic Programming",
- booktitle = "Australasia-Japan Workshop on Intelligent and Evolutionary Systems",
- pages = "45--51",
- year = "2001",
- editor = "Nikola Kasabov and Peter Whigham",
- address = "University of Otago, Dunedin, New Zealand",
- month = "19-21st " # nov,
- keywords = "genetic algorithms, genetic programming, committee learning, fitness sharing, anti-correlation, population diversity",
-
URL = "
http://sc.snu.ac.kr/PAPERS/AJ01.pdf",
-
URL = "
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.9515",
- size = "7 pages",
- abstract = "We compare three diversity-preserving mechanisms, implicit fitness sharing, negative correlation learning, and a new form, root-quartic negative correlation learning, on a standard genetic programming problem, the 6multiplexer. On this problem, root-quartic negative correlation learning significantly outperforms standard negative correlation learning, and marginally outperforms implicit fitness sharing. We analyse the difference between standard and root-quartic negative correlation learning, and provide a partial explanation for the improved performance.",
-
notes = "6-MUX DCTG-GP
broken Nov 2012 http://divcom.otago.ac.nz/infosci/KEL/conferences/IESWorkshop/default.htm
Perhaps also McKay, R I and Abbass H.A. 'Anti-correlation: A Diversity Promoting Mechanisms in Ensemble Learning'. The Australian Journal of Intelligent Information Processing Systems 7(3/4), 2001, Pp 139 - 149 \cite{McKay:2001:AJIIPS_2}.",
