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

How to teach Deep Blue to play poker and deliver groceries
http://bit.ly/1DXGeZD
I have published some papers on timetabling.
http://bit.ly/hSGAhZ

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

What is your Erdös Number?

Publication(s)

Solving Multi-objective Optimisation Problems Using the Potential Pareto Regions Evolutionary Algorithm
http://bit.ly/fCOMDK
Evolving Tiles for Automated Self-Assembly Design
http://bit.ly/dInbHL
Regulators as Ďagentsí: power and personality in risk regulation and a role for agent-based simulation
http://bit.ly/evaXWn
Iterated Local Search vs. Hyper-heuristics: Towards General-Purpose Search Algorithms
http://bit.ly/gWFcuw

Graham Kendall: Details of Requested Publication


Citation

Oates, R; Kendall, G and Garibaldi, J. M The Limitations of Frequency Analysis for Dendritic Cell Population Modelling. In Proceedings of the 7th international conference on Artificial Immune Systems (ICARIS 2008), pages 328-339, 10-13 August 2008, Phuket, Thailand, Lecture Notes in Computer Science 5132, 2008.


Abstract

In previous work we derived a mathematical model which allows the frequency response of a dendritic cell to be predicted. The model has three, key limitations: the model assumes that the intermediate co stimulatory molecule signal is constant; it is only possible to make predictions for a single cell and the model only takes into account the signal processing element of the dendritic cell algorithm, with no attempt to explore the antigen presenting phase. In this paper we explore the original model and attempt to extend it to include the effects of multiple cells. It is found that the complex interactions between the cells creates a one to many relationship between the input frequency and the output frequency. This suggests that traditional frequency-based techniques alone are unlikely to yield an effective automated tuning mechanism.


pdf

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doi

The doi for this publication is 10.1007/978-3-540-85072-4_29 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

The URL for additional information is http://dx.doi.org/10.1007/978-3-540-85072-4

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{okg2008a, author = {R. Oates and G. Kendall and J. M. Garibaldi},
title = {The Limitations of Frequency Analysis for Dendritic Cell Population Modelling},
booktitle = {Proceedings of the 7th international conference on Artificial Immune Systems (ICARIS 2008)},
year = {2008},
editor = {P. J. Bentley and D. Lee and S. Jung},
volume = {5132},
series = {Lecture Notes in Computer Science},
pages = {328--339},
address = {10-13 August 2008, Phuket, Thailand},
abstract = {In previous work we derived a mathematical model which allows the frequency response of a dendritic cell to be predicted. The model has three, key limitations: the model assumes that the intermediate co stimulatory molecule signal is constant; it is only possible to make predictions for a single cell and the model only takes into account the signal processing element of the dendritic cell algorithm, with no attempt to explore the antigen presenting phase. In this paper we explore the original model and attempt to extend it to include the effects of multiple cells. It is found that the complex interactions between the cells creates a one to many relationship between the input frequency and the output frequency. This suggests that traditional frequency-based techniques alone are unlikely to yield an effective automated tuning mechanism.},
doi = {10.1007/978-3-540-85072-4_29},
keywords = {Artificial Immune Sytems, AIS, Dendrtic Cell, DCA, Population Modelling},
owner = {rxj},
timestamp = {2008.09.10},
url = {http://dx.doi.org/10.1007/978-3-540-85072-4},
webpdf = {http://www.graham-kendall.com/papers/okg2008a.pdf} }