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 blog occasionally, feel free to take a look.
http://bit.ly/hq6rMK
How to teach Deep Blue to play poker and deliver groceries
http://bit.ly/1DXGeZD

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Wisdom of the Crowds at the Graduate School Christmas Party

Publication(s)

A nozzle selection heuristic to optimise the hybrid pick and place machine
http://bit.ly/eAjsEX
A Multiobjective Approach for UK Football Scheduling
http://bit.ly/fV4caa
A local search approach to a circle cutting problem arising in the motor cycle industry
http://bit.ly/dJxzGW
A Multiobjective Approach for UK Football Scheduling
http://bit.ly/fV4caa

Graham Kendall: Details of Requested Publication


Citation

Li, J; Kendall, G and John, R Computing Nash Equilibria and Evolutionarily Stable States of Evolutionary Games. IEEE Transactions on Evolutionary Computation, 20 (3): 460-469, 2016.


Abstract

Stability analysis is an important research direction in evolutionary game theory. Evolutionarily stable states have a close relationship with Nash equilibria of repeated games, which are characterized by the folk theorem. When applying the folk theorem, one needs to compute the minimax profile of the game in order to find Nash equilibria. Computing the minimax profile is an NP-hard problem. In this paper, we investigate a new methodology to compute evolutionary stable states based on the level- $k$ equilibrium, a new refinement of Nash equilibrium in repeated games. A level- $k$ equilibrium is implemented by a group of players who adopt reactive strategies and who have no incentive to deviate from their strategies simultaneously. Computing the level- $k$ equilibria is tractable because the minimax payoffs and strategies are not needed. As an application, this paper develops a tractable algorithm to compute the evolutionarily stable states and the Pareto front of $n$ -player symmetric games. Three games, including the iterated prisonerís dilemma, are analyzed by means of the proposed methodology.


pdf

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doi

The doi for this publication is 10.1109/TEVC.2015.2490076 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 (3.654), 2013 (5.545), 2012 (4.810), 2011 (3.341), 2010 (4.403), 2009 (4.589), 2008 (3.736), 2007 (2.426), 2006 (3.770), 2005 (3.257), 2004 (3.688), 2003 (2.713), 2002 (1.486), 2001 (1.708)

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{lkj2016, author = {J. Li and G. Kendall and R. John},
title = {Computing Nash Equilibria and Evolutionarily Stable States of Evolutionary Games},
journal = {IEEE Transactions on Evolutionary Computation},
year = {2016},
volume = {20},
pages = {460--469},
number = {3},
abstract = {Stability analysis is an important research direction in evolutionary game theory. Evolutionarily stable states have a close relationship with Nash equilibria of repeated games, which are characterized by the folk theorem. When applying the folk theorem, one needs to compute the minimax profile of the game in order to find Nash equilibria. Computing the minimax profile is an NP-hard problem. In this paper, we investigate a new methodology to compute evolutionary stable states based on the level- ${k}$ equilibrium, a new refinement of Nash equilibrium in repeated games. A level- ${k}$ equilibrium is implemented by a group of players who adopt reactive strategies and who have no incentive to deviate from their strategies simultaneously. Computing the level- ${k}$ equilibria is tractable because the minimax payoffs and strategies are not needed. As an application, this paper develops a tractable algorithm to compute the evolutionarily stable states and the Pareto front of ${n}$ -player symmetric games. Three games, including the iterated prisonerís dilemma, are analyzed by means of the proposed methodology.},
doi = {10.1109/TEVC.2015.2490076},
issn = {1089-778X},
keywords = {Prisoners dilemma, iterated prisoners dilemma, strategy},
owner = {gxk},
timestamp = {2010.10.12},
webpdf = {http://www.graham-kendall.com/papers/lkj2016.pdf} }