- author = "Peter Lichodzijewski and Malcolm I. Heywood",
- title = "Pareto-coevolutionary genetic programming for problem decomposition in multi-class classification",
- booktitle = "GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation",
- year = "2007",
- editor = "Dirk Thierens and Hans-Georg Beyer and Josh Bongard and Jurgen Branke and John Andrew Clark and Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and Julian F. Miller and Jason Moore and Frank Neumann and Martin Pelikan and Riccardo Poli and Kumara Sastry and Kenneth Owen Stanley and Thomas Stutzle and Richard A Watson and Ingo Wegener",
- volume = "1",
- isbn13 = "978-1-59593-697-4",
- pages = "464--471",
- address = "London",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p464.pdf",
-
DOI = "
doi:10.1145/1276958.1277058",
- publisher = "ACM Press",
- publisher_address = "New York, NY, USA",
- month = "7-11 " # jul,
- organisation = "ACM SIGEVO (formerly ISGEC)",
- keywords = "genetic algorithms, genetic programming, Coevolution, problem decomposition, subset selection, supervised learning, training efficiency",
- abstract = "A bid-based approach for coevolving Genetic Programming classifiers is presented. The approach Co-evolves a population of learners that decompose the instance space by way of their aggregate bidding behaviour. To reduce computation overhead, a small, relevant, subset of training exemplars is (competitively) coevolved alongside the learners. The approach solves multi-class problems using a single population and is evaluated on three large datasets. It is found to be competitive, especially compared to classifier systems, while significantly reducing the computation overhead associated with training.",
-
notes = "GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).
ACM Order Number 910071",
