Graham Kendall
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Professor Graham Kendall

Professor Graham Kendall is the Provost and CEO of The University of Nottingham Malaysia Campus (UNMC). He is also a Pro-Vice Chancellor of the University of Nottingham.

He is a Director of MyResearch Sdn Bhd, Crops for the Future Sdn Bhd. and Nottingham Green Technologies Sdn Bhd. He is a Fellow of the British Computer Society (FBCS) and a Fellow of the Operational Research Society (FORS).

He has published over 230 peer reviewed papers. He is an Associate Editor of 10 journals and the Editor-in-Chief of the IEEE Transactions of Computational Intelligence and AI in Games.

News

I blog occasionally, feel free to take a look.
http://bit.ly/hq6rMK
I have wriiten a number of articles for TheConversation
http://bit.ly/1yWlOkE

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Can Forecasters Forecast Successfully?: Evidence from UK Betting Markets

Publication(s)

Sports Scheduling: Minimizing Travel for English Football Supporters
RATE_LIMIT_EXCEEDED
A Strategy with Novel Evolutionary Features for the Iterated Prisoner's Dilemma
RATE_LIMIT_EXCEEDED
A hyper-heuristic approach to sequencing by hybridization of DNA sequences
RATE_LIMIT_EXCEEDED
Iterated Local Search vs. Hyper-heuristics: Towards General-Purpose Search Algorithms
RATE_LIMIT_EXCEEDED

Graham Kendall: Details of Requested Publication


Citation

Burke, E. K; Gustafson, S; Kendal, G and Krasnogor, N Is increased diversity in genetic programming beneficial? An analysis of lineage selection. In Proceedings of the The IEEE 2003 Congress on Evolutionary Computation (CEC2003), pages 1398-1405, Canberra, Australia, 2003.


Abstract

This paper presents an analysis of increased diversity in genetic programming. A selection strategy based on genetic lineages is used to increase genetic diversity. A genetic lineage is defined as the path from an individual to individuals which were created from its genetic material. The method is applied to three problem domains: artificial ant, even-5-parity and symbolic regression of the binomial-3 function. We examine how increased diversity affects problems differently and draw conclusions about the types of diversity which are more important for each problem. Results indicate that diversity in the ant problem helps to overcome deception, while elitism in combination with diversity is likely to benefit the parity and regression problems.


pdf

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doi

The doi for this publication is 10.1109/CEC.2003.1299834 You can link directly to the original paper, via the doi, from here

What is a doi?: A doi (Document Object Identifier) is a unique identifier for sicientific papers (and occasionally other material). This provides direct access to the location where the original article is published using the URL http://dx.doi/org/xxxx (replacing xxx with the doi). See http://dx.doi.org/ for more information



URL

This pubication does not have a URL associated with it.

The URL is only provided if there is additional information that might be useful. For example, where the entry is a book chapter, the URL might link to the book itself.


Bibtex

@INPROCEEDINGS{bgkn2003, author = {E. K. Burke and S. Gustafson and G. Kendal and N. Krasnogor},
title = {Is increased diversity in genetic programming beneficial? An analysis of lineage selection},
booktitle = {Proceedings of the The IEEE 2003 Congress on Evolutionary Computation (CEC2003)},
year = {2003},
volume = {2},
pages = {1398--1405},
address = {Canberra, Australia},
month = {December 8-12},
abstract = {This paper presents an analysis of increased diversity in genetic programming. A selection strategy based on genetic lineages is used to increase genetic diversity. A genetic lineage is defined as the path from an individual to individuals which were created from its genetic material. The method is applied to three problem domains: artificial ant, even-5-parity and symbolic regression of the binomial-3 function. We examine how increased diversity affects problems differently and draw conclusions about the types of diversity which are more important for each problem. Results indicate that diversity in the ant problem helps to overcome deception, while elitism in combination with diversity is likely to benefit the parity and regression problems.},
comment = {IEEE Catalog Number: 03TH8674, ISBN: 0-7803-7804-0},
doi = {10.1109/CEC.2003.1299834},
keywords = {genetic programming, artificial ant, symbolic regression},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/bgkn2003.pdf} }