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 the chair of the MISTA (Multidisciplinary International Conference on Scheduling: Theory and Applications)
http://bit.ly/hvZIaN
How are football fixtures worked out?
http://bit.ly/1z0oTAH

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

MISTA Conference: Venue for 2011 announced

Publication(s)

Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming
http://bit.ly/2k79ATE
A Multi-objective Hyper-heuristic based on Choice Function
http://bit.ly/1f8GQgU
A scheme for determining vehicle routes based on Arc-based service network design
http://bit.ly/2iaUTxA
Evolving Reusable 3D Packing Heuristics with Genetic Programming.
http://bit.ly/e75y7F

Graham Kendall: Details of Requested Publication


Citation

Hingston, P and Kendall, G Learning versus Evolution in Iterated Prisoner's Dilemma. In Proceedings of the 2004 IEEE Congress on Evolutionary Computation (CEC'04), pages 364-372, Portland, Oregon, 2004.


Abstract

In this paper, we explore interactions in a co-evolving population of model-based adaptive agents and fixed non-adaptive agents playing the iterated prisoner's dilemma (IPD). The IPD is much studied in the game theory, machine learning and evolutionary computation communities as a model of emergent cooperation between self-interested individuals. Each field poses the players' task in its own way, making different assumptions about the degree of rationality of the players and their knowledge of the structure of the game, and whether learning takes place at the group (evolutionary) level or at the individual level. In this paper, we report on a simulation study that attempts to bridge these gaps. In our simulations, we find that a kind of equilibrium emerges, with a smaller number of adaptive agents surviving by exploiting a larger number of non-adaptive ones.


pdf

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doi

The doi for this publication is 10.1109/CEC.2004.1330880 You can link directly to the original paper, via the doi, from here

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URL

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Bibtex

@INPROCEEDINGS{hk2004, author = {P. Hingston and G. Kendall},
title = {Learning versus Evolution in Iterated Prisoner's Dilemma},
booktitle = {Proceedings of the 2004 IEEE Congress on Evolutionary Computation (CEC'04)},
year = {2004},
pages = {364--372},
address = {Portland, Oregon},
month = {20-23 June},
abstract = {In this paper, we explore interactions in a co-evolving population of model-based adaptive agents and fixed non-adaptive agents playing the iterated prisoner's dilemma (IPD). The IPD is much studied in the game theory, machine learning and evolutionary computation communities as a model of emergent cooperation between self-interested individuals. Each field poses the players' task in its own way, making different assumptions about the degree of rationality of the players and their knowledge of the structure of the game, and whether learning takes place at the group (evolutionary) level or at the individual level. In this paper, we report on a simulation study that attempts to bridge these gaps. In our simulations, we find that a kind of equilibrium emerges, with a smaller number of adaptive agents surviving by exploiting a larger number of non-adaptive ones.},
doi = {10.1109/CEC.2004.1330880},
keywords = {iterated prisoner's dilemma, evolution, coevolution, co-evolution, game theory, machine learning, agents, iterated prisoners dilemma},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/hk2004.pdf} }