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 have wriiten a number of articles for TheConversation
http://bit.ly/1yWlOkE
What do we spend so much in supermarkets?
http://bit.ly/1yW6If7

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Football Prediction: A decision to be made

Publication(s)

Heuristic Space Diversity Control for Improved Meta-Hyper-Heuristic Performance
http://bit.ly/1C1vIAn
Co-evolution of Successful Trading Strategies in A Simulated Stock Market
http://bit.ly/eAkoXn
A Hyperheuristic Approach to Scheduling a Sales Summit
http://bit.ly/f5PRaP
Hyper-Heuristics: An Emerging Direction in Modern Search Technology
http://bit.ly/1goVsLe

Graham Kendall: Details of Requested Publication


Citation

Chong, S. Y; Humble, J; Kendall, G; Li, J and Yao, X Chapter 3: Learning IPD Strategies through Coevolution. In The Iterated Prisoners' Dilemma: 20 Years On, pages 63-87, World Scientific, Singapore, Advances in Natural Computation 4, 2007.


Abstract

The game of the iterated prisonerís dilemma (IPD) has been a popular metaphor in explaining cooperative behaviors among selfish individuals. There are several frameworks for which the IPD behavioral interactions can be modelled, depending on the context in question. With the co-evolutionary learning framework, emphasis is placed on studying the conditions of how and why certain IPD behaviors can be learned through a process of adaptation on a strategy representation of behaviors based solely on strategy interactions (i.e., game-play). This framework is different from the classical evolutionary game theory framework that is concerned with frequency dependent reproduction of fixed and predetermined strategies. This review aims at providing a survey of studies on the IPD using the co-evolutionary learning approach. In particular, studies that extended the classical IPD game with two players and two choices are presented.


pdf

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doi

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URL

The URL for additional information is http://www.worldscibooks.com/economics/6461.html

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Bibtex

@INBOOK{chkly2007c, chapter = {The Iterated Prisoners' Dilemma: 20 Years On},
pages = {63--87},
title = {Chapter 3: Learning IPD Strategies through Coevolution},
publisher = {World Scientific, Singapore},
year = {2007},
editor = {G. Kendall and X. Yao and S. Y. Chong},
author = {S. Y. Chong and J. Humble and G. Kendall and J. Li and X. Yao},
volume = {4},
number = {3},
series = {Advances in Natural Computation},
abstract = {The game of the iterated prisonerís dilemma (IPD) has been a popular metaphor in explaining cooperative behaviors among selfish individuals. There are several frameworks for which the IPD behavioral interactions can be modelled, depending on the context in question. With the co-evolutionary learning framework, emphasis is placed on studying the conditions of how and why certain IPD behaviors can be learned through a process of adaptation on a strategy representation of behaviors based solely on strategy interactions (i.e., game-play). This framework is different from the classical evolutionary game theory framework that is concerned with frequency dependent reproduction of fixed and predetermined strategies. This review aims at providing a survey of studies on the IPD using the co-evolutionary learning approach. In particular, studies that extended the classical IPD game with two players and two choices are presented.},
keywords = {IPD, Iterated Prisoners; Dilemma, Co-evolution},
owner = {jvb},
timestamp = {2008.09.30},
url = {http://www.worldscibooks.com/economics/6461.html},
webpdf = {http://www.graham-kendall.com/papers/chkly2007c.pdf} }