Identifying two piecewise linear additive value functions from anonymous preference information
Artificial Intelligence
2026-02-25 v1
Abstract
Eliciting a preference model involves asking a person, named decision-maker, a series of questions. We assume that these preferences can be represented by an additive value function. In this work, we query simultaneously two decision-makers in the aim to elicit their respective value functions. For each query we receive two answers, without noise, but without knowing which answer corresponds to which decision-maker.We propose an elicitation procedure that identifies the two preference models when the marginal value functions are piecewise linear with known breaking points.
Keywords
Cite
@article{arxiv.2602.20638,
title = {Identifying two piecewise linear additive value functions from anonymous preference information},
author = {Vincent Auriau and Khaled Belahcene and Emmanuel Malherbe and Vincent Mousseau and Marc Pirlot},
journal= {arXiv preprint arXiv:2602.20638},
year = {2026}
}