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

Help solve Santa's logistics problems
http://bit.ly/1DXreuW
The hunt for MH370
http://bit.ly/1DXRLbu

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Videos on the basics of Java

Publication(s)

Making Airline Schedules More Robust
http://bit.ly/hbGm4B
Population based Local Search for university course timetabling problems
http://bit.ly/1mlJLZj
A novel approach to independent taxi scheduling problem based on stable matching
http://bit.ly/1A3GUfR
Scheduling TV Commercials: Models and Solution Methodologies
http://bit.ly/idSBCA

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K; Gustafson, S and Kendall, G A Puzzle to Challenge Genetic Programming. In Proceedings of the 5th European Conference on Genetic Programming (EURO-GP), pages 136-147, Springer-Verlag, Kinsale, Ireland, 3-4 April, Lecture Notes in Computer Science 2278, 2002.

The DOI link gives the page numbers as 136-147, the PDF show the page numbers as 238-247. We assume the DOI citation is correct (i.e. pages 136-147)


Abstract

This report represents an initial investigation into the use of genetic programming to solve the N-prisoners puzzle. The puzzle has generated a certain level of interest among the mathematical community. We believe that this puzzle presents a significant challenge to the field of evolutionary computation and to genetic programming in particular. The overall aim is to generate a solution that encodes complex decision making. Our initial results demonstrate that genetic programming can evolve good solutions. We compare these results to engineered solutions and discuss some of the implications. One of the consequences of this study is that it has highlighted a number of research issues and directions and challenges for the evolutionary computation community. We conclude the article by presenting some of these directions which range over several areas of evolutionary computation, including multi-objective fitness, coevolution and cooperation, and problem representations.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/3-540-45984-7_23 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

The URL for additional information is http://dx.doi.org/10.1007/3-540-45984-7

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{bgk2002, author = {E.K. Burke and S. Gustafson and G. Kendall},
title = {A Puzzle to Challenge Genetic Programming},
booktitle = {Proceedings of the 5th European Conference on Genetic Programming (EURO-GP)},
year = {2002},
editor = {J. Foster and E. Lotton and J. Liller and C. Ryan and A. Tettamanzi},
volume = {2278},
series = {Lecture Notes in Computer Science},
pages = {136--147},
address = {Kinsale, Ireland, 3-4 April},
publisher = {Springer-Verlag},
note = {The DOI link gives the page numbers as 136-147, the PDF show the page numbers as 238-247. We assume the DOI citation is correct (i.e. pages 136-147)},
abstract = {This report represents an initial investigation into the use of genetic programming to solve the N-prisoners puzzle. The puzzle has generated a certain level of interest among the mathematical community. We believe that this puzzle presents a significant challenge to the field of evolutionary computation and to genetic programming in particular. The overall aim is to generate a solution that encodes complex decision making. Our initial results demonstrate that genetic programming can evolve good solutions. We compare these results to engineered solutions and discuss some of the implications. One of the consequences of this study is that it has highlighted a number of research issues and directions and challenges for the evolutionary computation community. We conclude the article by presenting some of these directions which range over several areas of evolutionary computation, including multi-objective fitness, coevolution and cooperation, and problem representations.},
comment = {ISBN 3-540-43378-3, ISSN 0302-9743},
doi = {10.1007/3-540-45984-7_23},
keywords = {genetic programming, evolutionary computation},
timestamp = {2007.03.29},
url = {http://dx.doi.org/10.1007/3-540-45984-7},
webpdf = {http://www.graham-kendall.com/papers/bgk2002.pdf} }