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

Hüllermeier, Eyke und Słowiński, Roman (2024): Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies—part II. In: 4OR - A Quarterly Journal of Operations Research, Vol. 22, No. 3: pp. 313-349

Abstract

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.

• Item Type: Journal article
• Keywords: Artificial Intelligence
• Faculties: Mathematics, Computer Science and Statistics > Computer Science > Artificial Intelligence and Machine Learning
• Subjects: 000 Computer science, information and general works > 000 Computer science, knowledge, and systems
• ISSN: 1619-4500
• Language: English
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 438445824