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 am a member of the Automated Scheduling, Optimisation and Planning Research Group
http://bit.ly/eIQ5XC
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

3D Bin Packing, help Santa and share $10,000

Publication(s)

Population based Local Search for university course timetabling problems
http://bit.ly/1mlJLZj
Evolving Weights for a new UK Divisia.
http://bit.ly/fopoFg
Chapter 4: Genetic Algorithms
http://bit.ly/1h1JBCi
Backward Induction and Repeated Games With Strategy Constraints: An Inspiration From the Surprise Exam Paradox
http://bit.ly/1ib50Nd

Graham Kendall: Details of Requested Publication


Citation

Yaakob, R and Kendall, G An Integration of BP-Pool and Social Learning in the Opening of Go. In Proceedings of 2009 WRI World Congress on Computer Science and Information Engineering, pages 636-640, 2009.


Abstract

In this paper, we investigate an integration of a best population pool and social learning, utilising evolutionary neural networks. The experiments are divided into several intervals, and we keep the best player from each interval in the best population pool (BP-pool). Social learning allows poor performing players to learn from those players, which are playing at a higher level. The feed forward neural networks are evolved via evolution strategies and no knowledge is incorporated into the players. The evolved neural network players play against a rule-based player, Gondo, at the beginning of the match. The remainder of the games then copied by another Gondo and they continue the game by playing against themselves. Our results demonstrate that learning is taking place.


pdf

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doi

The doi for this publication is 10.1109/CSIE.2009.875 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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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{yk2009, author = {R. Yaakob and G. Kendall},
title = {An Integration of BP-Pool and Social Learning in the Opening of Go},
booktitle = {Proceedings of 2009 WRI World Congress on Computer Science and Information Engineering},
year = {2009},
pages = {636--640},
abstract = {In this paper, we investigate an integration of a best population pool and social learning, utilising evolutionary neural networks. The experiments are divided into several intervals, and we keep the best player from each interval in the best population pool (BP-pool). Social learning allows poor performing players to learn from those players, which are playing at a higher level. The feed forward neural networks are evolved via evolution strategies and no knowledge is incorporated into the players. The evolved neural network players play against a rule-based player, Gondo, at the beginning of the match. The remainder of the games then copied by another Gondo and they continue the game by playing against themselves. Our results demonstrate that learning is taking place.},
doi = {10.1109/CSIE.2009.875},
owner = {Graham},
timestamp = {2016.02.07},
webpdf = {http://www.graham-kendall.com/papers/yk2009.pdf} }