Graham Kendall
Various Images

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

If you are interested in hyper-heuristics, take a look at my publications in this area
http://bit.ly/efxLGg
I have published a number of papers on Cutting and Packing
http://bit.ly/dQPw7T

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

How Isaac Newton could help you beat the casino at roulette

Publication(s)

Comparison of meta-heuristic algorithms for clustering rectangles
http://bit.ly/eQQ0Kd
Repeated Goofspiel: A Game of Pure Strategy
http://bit.ly/1hWAFiz
Hyper-heuristics: a survey of the state of the art
http://bit.ly/1eSDAeb
Choice Function and Random HyperHeuristics
http://bit.ly/e7QYog

Graham Kendall: Details of Requested Publication


Citation

Oates, R; Kendall, G and Garibaldi, J.M Frequency analysis for dendritic cell population tuning. Evolutionary Intelligence, 1 (2): 145-157, 2008.


Abstract

The dendritic cell algorithm (DCA) has been applied successfully to a diverse range of applications. These applications are related by the inherent uncertainty associated with sensing the application environment. The DCA has performed well using unfiltered signals from each environment as inputs. In this paper we demonstrate that the DCA has an emergent filtering mechanism caused by the manner in which the cell accumulates its internal variables. Furthermore we demonstrate a relationship between the migration threshold of the cells and the transfer function of the algorithm. A tuning methodology is proposed and a robotic application published previously is revisited using the new tuning technique.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/s12065-008-0011-y 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



URL

This pubication does not have a URL associated with it.

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{okg2008, author = {R. Oates and G. Kendall and J.M. Garibaldi},
title = {Frequency analysis for dendritic cell population tuning},
journal = {Evolutionary Intelligence},
year = {2008},
volume = {1},
pages = {145--157},
number = {2},
abstract = {The dendritic cell algorithm (DCA) has been applied successfully to a diverse range of applications. These applications are related by the inherent uncertainty associated with sensing the application environment. The DCA has performed well using unfiltered signals from each environment as inputs. In this paper we demonstrate that the DCA has an emergent filtering mechanism caused by the manner in which the cell accumulates its internal variables. Furthermore we demonstrate a relationship between the migration threshold of the cells and the transfer function of the algorithm. A tuning methodology is proposed and a robotic application published previously is revisited using the new tuning technique.},
doi = {10.1007/s12065-008-0011-y},
issn = {1864-5909},
keywords = {Dendritic cell, Robotics, Artificial Immune Systems},
owner = {rxj},
timestamp = {2008.09.10},
webpdf = {http://www.graham-kendall.com/papers/okg2008.pdf} }