Graham Kendall
Various Images

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 university examinations scheduled?
http://bit.ly/1z0pG4s
I have published some papers on timetabling.
http://bit.ly/hSGAhZ

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Bibtex: How to enter names

Publication(s)

A great deluge algorithm for a real-world examination timetabling problem
http://bit.ly/1xCdCSx
Chapter 1: Introduction
http://bit.ly/1goQv51
Constructing Initial Neighbourhoods to Identify Critical Constraints
http://bit.ly/h3xfnd
An efficient and robust approach to generate high quality solutions for the Traveling Tournament Problem.
http://bit.ly/fCqNU6

Graham Kendall: Details of Requested Publication


Citation

Davis, J.E and Kendall, G An Investigation, using Co-Evolution, to Evolve an Awari Player. In Proceedings of the 2002 Congress on Evolutionary Computation (CEC 2002), pages 1408-1413, Hilton Hawaiian Village Hotel, Honolulu, Hawaii, May 12-17, 2002.


Abstract

Awari is a two-player game of perfect information, played using 12 “pits” and 48 seeds or stones. The aim is for one player to capture more than half the seeds. In this work we show how an awari player can be evolved using a co-evolutionary approach where computer players play against one another, with the strongest players surviving and being mutated using an evolutionary strategy (ES). The players are represented using a simple evaluation function, representing the current game state, with each term of the function having a weight which is evolved using the ES. The output of the evaluation function is used in a mini-max search. We play the best evolved player against one of the strongest shareware programs (Awale) and are able to defeat the program at three of its four levels of play.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1109/CEC.2002.1004449 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{dk2002, author = {J.E. Davis and G. Kendall},
title = {An Investigation, using Co-Evolution, to Evolve an Awari Player},
booktitle = {Proceedings of the 2002 Congress on Evolutionary Computation (CEC 2002)},
year = {2002},
pages = {1408--1413},
address = {Hilton Hawaiian Village Hotel, Honolulu, Hawaii, May 12-17},
abstract = {Awari is a two-player game of perfect information, played using 12 “pits” and 48 seeds or stones. The aim is for one player to capture more than half the seeds. In this work we show how an awari player can be evolved using a co-evolutionary approach where computer players play against one another, with the strongest players surviving and being mutated using an evolutionary strategy (ES). The players are represented using a simple evaluation function, representing the current game state, with each term of the function having a weight which is evolved using the ES. The output of the evaluation function is used in a mini-max search. We play the best evolved player against one of the strongest shareware programs (Awale) and are able to defeat the program at three of its four levels of play.},
comment = {ISBN 0-7803-7282-4},
doi = {10.1109/CEC.2002.1004449},
keywords = {Games, Awari, evolution strategy, co-evolution, coevolution},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/dk2002.pdf} }