Targeting in Multi-Criteria Decision Making

Authors

  • Nicolas Schwind AIST, National Institute of Advanced Industrial Science and Technology, Tokyo
  • Patricia Everaere CRIStAL, CNRS - Université de Lille
  • Sébastien Konieczny CRIL, CNRS - Université d'Artois
  • Emmanuel Lonca CRIL, CNRS - Université d'Artois

DOI:

https://doi.org/10.1609/aaai.v40i43.40998

Abstract

In this work, we introduce the notion of targeting for multi-criteria decision making. The problem involves selecting the best alternatives related to one particular alternative, called the target. We use an axiomatic approach to this problem by establishing properties that any targeting method should satisfy. We present a representation theorem and show that satisfying the main properties of targeting requires aggregating the evaluations of the alternatives related to the target. We propose various candidate targeting methods and examine the properties satisfied by each method.

Published

2026-03-14

How to Cite

Schwind, N., Everaere, P., Konieczny, S., & Lonca, E. (2026). Targeting in Multi-Criteria Decision Making. Proceedings of the AAAI Conference on Artificial Intelligence, 40(43), 36732–36739. https://doi.org/10.1609/aaai.v40i43.40998

Issue

Section

AAAI Technical Track on Reasoning under Uncertainty