Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)

Holistic Preference Learning with the Choquet Integral

Authors
Bénédicte Goujon, Christophe Labreuche
Corresponding Author
Bénédicte Goujon
Available Online August 2013.
DOI
https://doi.org/10.2991/eusflat.2013.13How to use a DOI?
Keywords
Preference Learning Multi-criteria Decision Model Choquet Integral Fixed-point
Abstract
The current approaches to construct a multi-criteria model based on a Choquet integral are split into two separate steps: construct first the utility functions and then the aggregation function. Unfortunately, the decision maker may feel some difficulties in addressing these tricky steps. In this paper, we propose a preference learning algorithm that construct both the utility functions and the capacity from several preferences or evaluations. The algorithm is based on a fixed-point approach that transforms the global optimization learning problem into two iterative linear problems. Each problem objective is to minimize the number of non validated learning examples.
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Volume Title
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
Series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-78-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/eusflat.2013.13How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Bénédicte Goujon
AU  - Christophe Labreuche
PY  - 2013/08
DA  - 2013/08
TI  - Holistic Preference Learning with the Choquet Integral
BT  - Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 88
EP  - 95
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.13
DO  - https://doi.org/10.2991/eusflat.2013.13
ID  - Goujon2013/08
ER  -