Computational modelling for decision-making: where, why, what, who and how

被引：80

作者：

Calder, Muffy ^{[1
]}

Craig, Claire ^{[2
]}

Culley, Dave ^{[3
]}

de Cani, Richard ^{[4
]}

Donnelly, Christl A. ^{[5
]}

Douglas, Rowan ^{[6
]}

Edmonds, Bruce ^{[7
]}

Gascoigne, Jonathon ^{[6
]}

Gilbert, Nigel ^{[8
]}

Hargrove, Caroline ^{[9
]}

Hinds, Derwen ^{[10
]}

Lane, David C. ^{[11
]}

Mitchell, Dervilla ^{[4
]}

Pavey, Giles

Robertson, David ^{[12
]}

Rosewell, Bridget ^{[13
]}

Sherwin, Spencer ^{[14
]}

Walport, Mark ^{[15
]}

Wilson, Alan ^{[16
]}

机构：

[1] Univ Glasgow, Sch Comp Sci, Glasgow, Lanark, Scotland

[2] Royal Soc, London, England

[3] Improbable, London, England

[4] Arup, London, England

[5] Imperial Coll London, MRC Ctr Global Infect Dis Anal, Dept Infect Dis Epidemiol, London, England

[6] Willis Towers Watson, London, England

[7] Manchester Metropolitan Univ, Ctr Policy Modelling, Manchester, Lancs, England

[8] Univ Surrey, Ctr Res Social Simulat, Guildford, Surrey, England

[9] McLaren Appl Technol, Woking, Surrey, England

[10] Natl Cyber Secur Ctr, London, England

[11] Univ Reading, Henley Business Sch, Reading, Berks, England

[12] Univ Edinburgh, Sch Informat, Edinburgh, Midlothian, Scotland

[13] Volterra Partners, London, England

[14] Imperial Coll London, Dept Aeronaut, London, England

[15] UK Res & Innovat, London, England

[16] Alan Turing Inst, London, England

来源：

ROYAL SOCIETY OPEN SCIENCE | 2018年 / 5卷 / 06期

基金：

英国医学研究理事会;

关键词：

modelling; decision-making; data; uncertainty; complexity; communication;

D O I：

10.1098/rsos.172096

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In order to deal with an increasingly complex world, we need ever more sophisticated computational models that can help us make decisions wisely and understand the potential consequences of choices. But creating a model requires far more than just raw data and technical skills: it requires a close collaboration between model commissioners, developers, users and reviewers. Good modelling requires its users and commissioners to understand more about the whole process, including the different kinds of purpose a model can have and the different technical bases. This paper offers a guide to the process of commissioning, developing and deploying models across a wide range of domains from public policy to science and engineering. It provides two checklists to help potential modellers, commissioners and users ensure they have considered the most significant factors that will determine success. We conclude there is a need to reinforce modelling as a discipline, so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling, so that the results are more useful.

引用

页数：15

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