- author = "Garnett Carl Wilson and Malcolm Iain Heywood",
- title = "Probabilistic (Genotype) Adaptive Mapping Combinations for Developmental Genetic Programming",
- booktitle = "Proceedings of the 2006 IEEE Congress on Evolutionary Computation",
- year = "2006",
- editor = "Gary G. Yen and Simon M. Lucas and Gary Fogel and Graham Kendall and Ralf Salomon and Byoung-Tak Zhang and Carlos A. Coello Coello and Thomas Philip Runarsson",
- pages = "2498--2505",
- address = "Vancouver, BC, Canada",
- month = "16-21 " # jul,
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "0-7803-9487-9",
-
URL = "
http://ieeexplore.ieee.org/servlet/opac?punumber=11108",
-
DOI = "
doi:10.1109/CEC.2006.1688619",
- abstract = "In development genetic programming (DGP) approaches where the search space is divided into genotypes and phenotypes, a mapping (or genetic code) is needed to connect the two spaces. This model has subsequently been extended so that mappings evolve, and recently an implementation was proposed that co-evolves a genotype population and a population of adaptive mappings. Here, the authors identify and investigate performance obstacles for this recent implementation. They then introduce a new probabilistic adaptive mapping DGP that avoids those performance problems and explores a greater search space of genotype-mapping combinations without significant computational expense. The algorithm is shown to be more robust and to outperform the comparison adaptive mapping algorithm on challenging settings of the chosen test benchmark.",
-
notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
the IEE.
IEEE Catalog Number: 06TH8846D",
