An Axiomatic Approach to Revising Preferences

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Abstract

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.
Originalspracheenglisch
TitelProceedings AAAI 2022
Herausgeber (Verlag)AAAI Press
Seiten5676-5683
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung36th AAAI Conference on Artificial Intelligence: AAAI 2022 - Vancouver, Kanada
Dauer: 22 Feb. 20221 März 2022

Konferenz

Konferenz36th AAAI Conference on Artificial Intelligence
KurztitelAAAI 2022
Land/GebietKanada
OrtVancouver
Zeitraum22/02/221/03/22

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