Identifying two piecewise linear additive value functions from anonymous preference information
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866918353398923264 |
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| author | Auriau, Vincent Belahcene, Khaled Malherbe, Emmanuel Mousseau, Vincent Pirlot, Marc |
| author_facet | Auriau, Vincent Belahcene, Khaled Malherbe, Emmanuel Mousseau, Vincent Pirlot, Marc |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_20638 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Identifying two piecewise linear additive value functions from anonymous preference information Auriau, Vincent Belahcene, Khaled Malherbe, Emmanuel Mousseau, Vincent Pirlot, Marc Artificial Intelligence 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. |
| title | Identifying two piecewise linear additive value functions from anonymous preference information |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2602.20638 |