Professor Matthias Troffaes matthias.troffaes@durham.ac.uk
Professor
Imprecise swing weighting for multi-attribute utility elicitation based on partial preferences
Troffaes, Matthias C.M.; Sahlin, Ullrika
Authors
Ullrika Sahlin
Contributors
Alessandro Antonucci
Editor
Giorgio Corani
Editor
Inés Couso
Editor
Sébastien Destercke
Editor
Abstract
We describe a novel approach to multi-attribute utility elicitation which is both general enough to cover a wide range of problems, whilst at the same time simple enough to admit reasonably straightforward calculations. We allow both utilities and probabilities to be only partially specified, through bounding. We still assume marginal utilities to be precise. We derive necessary and sufficient conditions under which our elicitation procedure is consistent. As a special case, we obtain an imprecise generalization of the well known swing weighting method for eliciting multi-attribute utility functions. An example from ecological risk assessment demonstrates our method.
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | The Tenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’17) |
Start Date | Jul 10, 2017 |
End Date | Jul 14, 2017 |
Acceptance Date | Apr 17, 2017 |
Online Publication Date | Jun 20, 2017 |
Publication Date | Jun 20, 2017 |
Deposit Date | Mar 9, 2017 |
Publicly Available Date | May 15, 2017 |
Publisher | PMLR |
Pages | 333-345 |
Series Title | Proceedings of Machine Learning Research |
Series Number | 62 |
Series ISSN | 1938-7228 |
Book Title | Proceedings of the Tenth International Symposium on Imprecise Probability : Theories and Applications, 10-14 July 2017, Lugano (Switzerland). |
Public URL | https://durham-repository.worktribe.com/output/1149037 |
Publisher URL | http://proceedings.mlr.press/v62/troffaes17b.html |
Files
Accepted Conference Proceeding
(204 Kb)
PDF
You might also like
Regret-based budgeted decision rules under severe uncertainty
(2024)
Journal Article
A nonstandard approach to stochastic processes under probability bounding
(2023)
Conference Proceeding
A constructive theory for conditional lower previsions only using rational valued probability mass functions with finite support
(2023)
Presentation / Conference
Using probability bounding to improve decision making for offshore wind planning in industry
(2023)
Presentation / Conference
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search