Holistic Preference Learning with the Choquet Integral

DOI

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - 10.2991/eusflat.2013.13
ID  - Goujon2013/08
ER  -