An Axiomatic Approach to Revising Preferences

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We study a model of preference revision in which a prior preference over a set of alternatives is adjusted in order to accommodate input from an authoritative source, while maintaining certain structural constraints (e.g., transitivity, completeness), and without giving up more information than strictly necessary. We analyze this model under two aspects: the first allows us to capture natural distance-based operators, at the cost of a mismatch between the input and output formats of the revision operator. Requiring the input and output to be aligned yields a second type of operator, which we characterize using preferences on the comparisons in the prior preference Prefence revision is set in a logic-based framework and using the formal machinery of belief change, along the lines of the well-known AGM approach: we propose rationality postulates for each of the two versions of our model and derive representation results, thus situating preference revision within the larger family of belief change operators.
Original languageEnglish
Title of host publicationProceedings AAAI 2022
PublisherAAAI Press
Publication statusPublished - 2022
Event36th AAAI Conference on Artificial Intelligence: AAAI 2022 - Vancouver, Canada
Duration: 22 Feb 20221 Mar 2022


Conference36th AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI 2022


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