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

Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX
I blog occasionally, feel free to take a look.
http://bit.ly/hq6rMK

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Wisdom of the Crowds at the Graduate School Christmas Party

Publication(s)

A Tabu-Search Hyperheuristic for Timetabling and Rostering
http://bit.ly/i7823Y
The Cross-domain Heuristic Search Challenge - An International Research Competition
http://bit.ly/1a2VfMs
An Exponential Monte-Carlo Local Search Algorithm for the Berth Allocation Problem
http://bit.ly/1tLKIMh
Is increased diversity in genetic programming beneficial? An analysis of lineage selection
http://bit.ly/g0zaOT

Graham Kendall: Details of Requested Publication


Citation

Li, J; Hingston, P and Kendall, G Engineering Design of Strategies for Winning Iterated Prisonerís Dilemma Competitions. IEEE Transactions on Computational Intelligence and AI in Games, 3 (4): 348-360, 2011.


Abstract

In this paper, we investigate winning strategies for round-robin iterated Prisoner's Dilemma (IPD) competitions and evolutionary IPD competitions. Since the outcome of a single competition depends on the composition of the population of participants, we propose a statistical evaluation methodology that takes into account outcomes across varying compositions. We run several series of competitions in which the strategies of the participants are randomly chosen from a set of representative strategies. Statistics are gathered to evaluate the performance of each strategy. With this approach, the conditions for some well-known strategies to win a round-robin IPD competition are analyzed. We show that a strategy that uses simple rule-based identification mechanisms to explore and exploit the opponent outperforms well-known strategies such as tit-for-tat (TFT) in most round-robin competitions. Group strategies have an advantage over nongroup strategies in evolutionary IPD competitions. Group strategies adopt different strategies in interacting with kin members and nonkin members. A simple group strategy, Clique, which cooperates only with kin members, performs well in competing against well-known IPD strategies. We introduce several group strategies developed by combining Clique with winning strategies from round-robin competitions and evaluate their performance by adapting three parameters: sole survivor rate, extinction rate, and survival time. Simulation results show that these group strategies outperform well-known IPD strategies in evolutionary IPD competitions.


pdf

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doi

The doi for this publication is 10.1109/TCIAIG.2011.2166268 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


Journal Rankings


ISI Web of Knowledge Journal Citation Reports

The Web of Knowledge Journal Citation Reports (often known as ISI Impact Factors) help measure how often an article is cited. You can get an introduction to Journal Citation Reports here. Below I have provided the ISI impact factor for the jourrnal in which this article was published. For complete information I have shown the ISI ranking over a number of years, with the latest ranking highlighted.

2014 (1.481), 2013 (1.167), 2012 (1.694), 2011 (1.617)

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

@ARTICLE{lhk2011, author = {J. Li and P. Hingston and G. Kendall},
title = {Engineering Design of Strategies for Winning Iterated Prisonerís Dilemma Competitions},
journal = {IEEE Transactions on Computational Intelligence and AI in Games},
year = {2011},
volume = {3},
pages = {348--360},
number = {4},
abstract = {In this paper, we investigate winning strategies for round-robin iterated Prisoner's Dilemma (IPD) competitions and evolutionary IPD competitions. Since the outcome of a single competition depends on the composition of the population of participants, we propose a statistical evaluation methodology that takes into account outcomes across varying compositions. We run several series of competitions in which the strategies of the participants are randomly chosen from a set of representative strategies. Statistics are gathered to evaluate the performance of each strategy. With this approach, the conditions for some well-known strategies to win a round-robin IPD competition are analyzed. We show that a strategy that uses simple rule-based identification mechanisms to explore and exploit the opponent outperforms well-known strategies such as tit-for-tat (TFT) in most round-robin competitions. Group strategies have an advantage over nongroup strategies in evolutionary IPD competitions. Group strategies adopt different strategies in interacting with kin members and nonkin members. A simple group strategy, Clique, which cooperates only with kin members, performs well in competing against well-known IPD strategies. We introduce several group strategies developed by combining Clique with winning strategies from round-robin competitions and evaluate their performance by adapting three parameters: sole survivor rate, extinction rate, and survival time. Simulation results show that these group strategies outperform well-known IPD strategies in evolutionary IPD competitions.},
doi = {10.1109/TCIAIG.2011.2166268},
issn = {1943-068X},
keywords = {Prisoners dilemma, iterated prisoners dilemma, strategy},
owner = {gxk},
timestamp = {2010.10.12},
webpdf = {http://www.graham-kendall.com/papers/lhk2011.pdf} }