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

Does AI have a place in the board room?
http://bit.ly/1DXreuW
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

Football (Soccer) Prediction: Development Framework (#001)

Publication(s)

Alternative hyper-heuristic strategies for multi-method global optimization
http://bit.ly/g1xcMp
Automated code generation by local search
http://bit.ly/1dAz69a
Chapter 2: Iterated prisoner's dilemma and evolutionary game theory
http://bit.ly/1dhTcRf
An Integration of BP-Pool and Social Learning in the Opening of Go
http://bit.ly/1PtX9qq

Graham Kendall: Details of Requested Publication


Citation

Davies, G.J; Kendall, G; Soane, E; Li, J; Rocks, S.A; Jude, S.R and Pollard, S.J.T Regulators as agents: Modelling personality and power as evidence is brokered to support decisions on environmental risk. Science of the Total Environment, 466-467: 74-83, 2014.

ISSN: 0048-9697


Abstract

Complex regulatory decisions about risk rely on the brokering of evidence between providers and recipients, and involve personality and power relationships that influence the confidence that recipients may place in the sufficiency of evidence and, therefore, the decision outcome. We explore these relationships in an agent-based model; drawing on concepts from environmental risk science, decision psychology and computer simulation. A two-agent model that accounts for the sufficiency of evidence is applied to decisions about salt intake, animal carcass disposal and radioactive waste. A dynamic version of the model assigned personality traits to agents, to explore their receptivity to evidence. Agents with ‘aggressor’ personality sets were most able to imbue fellow agents with enhanced receptivity (with ‘avoider’ personality sets less so) and clear confidence in the sufficiency of evidence. In a dynamic version of the model, when both recipient and provider were assigned the ‘aggressor’ personality set, this resulted in 10 successful evidence submissions in 71 days, compared with 96 days when both agents were assigned the ‘avoider’ personality set. These insights suggest implications for improving the efficiency and quality of regulatory decision making by understanding the role of personality and power.


pdf

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doi

The doi for this publication is 10.1016/j.scitotenv.2013.06.116 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 (4.099), 2013 (3.163), 2012 (3.258), 2011 (3.286), 2010 (3.190), 2009 (2.905), 2008 (2.579), 2007 (2.182), 2006 (2.359), 2005 (2.224), 2004 (1.925), 2003 (1.455), 2002 (1.537), 2001 (1.396), 2000 (1.252)

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{dkslrjp2014, author = {G.J. Davies and G. Kendall and E. Soane and J. Li and S.A. Rocks and S.R. Jude and S.J.T. Pollard},
title = {Regulators as agents: Modelling personality and power as evidence is brokered to support decisions on environmental risk},
journal = {Science of the Total Environment},
year = {2014},
volume = {466-467},
pages = {74--83},
note = {ISSN: 0048-9697},
abstract = {Complex regulatory decisions about risk rely on the brokering of evidence between providers and recipients, and involve personality and power relationships that influence the confidence that recipients may place in the sufficiency of evidence and, therefore, the decision outcome. We explore these relationships in an agent-based model; drawing on concepts from environmental risk science, decision psychology and computer simulation. A two-agent model that accounts for the sufficiency of evidence is applied to decisions about salt intake, animal carcass disposal and radioactive waste. A dynamic version of the model assigned personality traits to agents, to explore their receptivity to evidence. Agents with ‘aggressor’ personality sets were most able to imbue fellow agents with enhanced receptivity (with ‘avoider’ personality sets less so) and clear confidence in the sufficiency of evidence. In a dynamic version of the model, when both recipient and provider were assigned the ‘aggressor’ personality set, this resulted in 10 successful evidence submissions in 71 days, compared with 96 days when both agents were assigned the ‘avoider’ personality set. These insights suggest implications for improving the efficiency and quality of regulatory decision making by understanding the role of personality and power.},
doi = {10.1016/j.scitotenv.2013.06.116},
issn = {0048-9697},
keywords = {Agents, Regulators. Modelling, Decision Making},
owner = {Graham},
timestamp = {2013.07.31},
webpdf = {http://www.graham-kendall.com/papers/dkslrjp2014.pdf} }