{"type":"ScholarlyArticle","title":"Incremental Elicitation of Rank-Dependent Aggregation Functions based on Bayesian Linear Regression","authors":[{"name":"Nadjet Bourdache","slug":"nadjet-bourdache","given":"Nadjet","family":"Bourdache","affiliation":"Sorbonne Université , CNRS , LIP6 , F-75005 Paris , France"},{"name":"Patrice Perny","slug":"patrice-perny","given":"Patrice","family":"Perny","affiliation":"Sorbonne Université , CNRS , LIP6 , F-75005 Paris , France"},{"name":"Olivier Spanjaard","slug":"olivier-spanjaard","given":"Olivier","family":"Spanjaard","affiliation":"Sorbonne Université , CNRS , LIP6 , F-75005 Paris , France"}],"abstract":"We introduce a new model-based incremental choice procedure for multicriteria decision support, that interleaves the analysis of the set of alternatives and the elicitation of weighting coefficients that specify the role of criteria in rank-dependent models such as ordered weighted averages (OWA) and Choquet integrals.  Starting from a prior distribution on the set of weighting parameters, we propose an adaptive elicitation approach based on the minimization of the expected regret to iteratively generate preference queries. The answers of the Decision Maker are used to revise the current distribution until a solution can be recommended with sufficient confidence. We present numerical tests showing the interest of the proposed approach.","doi":"10.24963/ijcai.2019/280","url":"https://ijcai.org/proceedings/2019/280","pdf":"https://ijcai.org/proceedings/2019/0280.pdf","markdown":"https://ijcai.org/proceedings/2019/280.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/280","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Machine Learning A-L","track":"Main track","number":280,"pages":{"first":2023,"last":2029},"keywords":["Knowledge Representation and Reasoning: Knowledge Representation and Decision ; Utility Theory","Machine Learning: Learning Preferences or Rankings","Multidisciplinary Topics and Applications: Recommender Systems"],"videos":[],"references":[{"position":1,"raw":"[Albert and Chib, 1993] James H Albert and Siddhartha Chib. 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