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

How are football fixtures worked out?
http://bit.ly/1z0oTAH
If you are interested in hyper-heuristics, take a look at my publications in this area
http://bit.ly/efxLGg

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Video Channels for Numbers, Periodic Tables, Deep Sky and all that is Molecular

Publication(s)

Memory Length in Hyper-heuristics: An Empirical Study
http://bit.ly/eXAo7v
Studying the Effect that a Linear Transformation has on the Time-Series Prediction Ability of an Evolutionary Neural Network
http://bit.ly/eyLaq2
A dynamic truck dispatching problem in marine container terminal
http://bit.ly/2mH037B
Problem Difficulty and Code Growth in Genetic Programming
http://bit.ly/eTibpi

Graham Kendall: Details of Requested Publication


Citation

Al-Khateeb, B and Kendall, G Introducing a Round Robin Tournament into Evolutionary Individual and Social Learning Checkers. In Proceedings of the Developments in E-systems Engineering (DeSE), pages 294-299, 2011.


Abstract

In recent years, much research attention has been paid to evolving self-learning game players. Fogel's Blondie24 is a demonstration of a real success in this field, inspiring many other scientists. In this paper, artificial neural networks are used as function evaluators in order to evolve game playing strategies for the game of checkers. We introduce a league structure into the learning phase of an individual and learning system based on the Blondie24 architecture. We show that this helps eliminate some of the randomness in the evolution. The best player we evolve is tested against an implementation of an evolutionary checkers program, and also against a player, which utilises the proposed round robin tournament and finally against an individual and social learning checkers program. The results are promising, suggesting many other research directions.


pdf

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doi

The doi for this publication is 10.1109/DeSE.2011.10 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

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Bibtex

@INPROCEEDINGS{ak2011b, author = {B. Al-Khateeb and G. Kendall},
title = {Introducing a Round Robin Tournament into Evolutionary Individual and Social Learning Checkers},
booktitle = {Proceedings of the Developments in E-systems Engineering (DeSE)},
year = {2011},
pages = {294--299},
month = {6-8 Dec 2011},
organization = {Sch. of Comput. Sci., Al-Anbar Univ., Ramadi, Iraq},
abstract = {In recent years, much research attention has been paid to evolving self-learning game players. Fogel's Blondie24 is a demonstration of a real success in this field, inspiring many other scientists. In this paper, artificial neural networks are used as function evaluators in order to evolve game playing strategies for the game of checkers. We introduce a league structure into the learning phase of an individual and learning system based on the Blondie24 architecture. We show that this helps eliminate some of the randomness in the evolution. The best player we evolve is tested against an implementation of an evolutionary checkers program, and also against a player, which utilises the proposed round robin tournament and finally against an individual and social learning checkers program. The results are promising, suggesting many other research directions.},
doi = {10.1109/DeSE.2011.10},
keywords = {Checkers, Blondie24, Draughts, Games, Computational Intelligence, Neural Networks, evolutionary computation},
owner = {gxk},
timestamp = {2010.12.11},
webpdf = {http://www.graham-kendall.com/papers/ak2011b.pdf} }