Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies – part II

Eyke Hüllermeier; Roman Słowiński

doi:10.1007/s10288-023-00561-5

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Title

Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies – part II

Authors

Eyke Hüllermeier
Roman Słowiński (WIiT) ^{[ 1 ][ 2.3 ][ P ]}

^{[ 1 ]} Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2024

Published in

4OR - A Quarterly Journal of Operations Research

Journal year: 2024 | Journal volume: in press

Article type

scientific article

Publication language

english

Keywords

EN

Preference learning
Preference modelling
Multiple criteria decision aiding
Multiple criteria decision making
Machine learning

Abstract

EN This article elaborates on the connection between multiple criteria decision aiding (MCDA) and preference learning (PL), two research fields with different roots and developed in different communities. It complements the first part of the paper, in which we started with a review of MCDA. In this part, a similar review will be given for PL, followed by a systematic comparison of both methodologies, as well as an overview of existing work on combining PL and MCDA. Our main goal is to stimulate further research at the junction of these two methodologies.

Date of online publication

30.01.2024

DOI

10.1007/s10288-023-00561-5

URL

https://link.springer.com/article/10.1007/s10288-023-00561-5

License type

CC BY (attribution alone)

Open Access Mode

czasopismo hybrydowe

Open Access Text Version

final published version