Abstract
The ability to measure the satisfaction of (groups of) voters is a crucial prerequisite for formulating proportionality axioms in approval-based participatory budgeting elections. Two common - but very different - ways to measure the satisfaction of a voter consider (i) the number of approved projects and (ii) the total cost of approved projects, respectively. In general, it is difficult to decide which measure of satisfaction best reflects the voters' true utilities. In this paper, we study proportionality axioms with respect to large classes of approval-based satisfaction functions. We establish logical implications among our axioms and related notions from the literature, and we ask whether outcomes can be achieved that are proportional with respect to more than one satisfaction function. We show that this is impossible for the two commonly used satisfaction functions when considering proportionality notions based on extended justified representation, but achievable for a notion based on proportional justified representation. For the latter result, we introduce a strengthening of priceability and show that it is satisfied by several polynomial-time computable rules, including the Method of Equal Shares and Phragmén's sequential rule.
Originalsprache | Englisch |
---|---|
Titel des Sammelwerks | Proceedings of the 37th AAAI Conference on Artificial Intelligence |
Untertitel des Sammelwerks | AAAI-23 Technical Tracks 5 |
Herausgeber*innen | Brian Williams, Yiling Chen, Jennifer Neville |
Erscheinungsort | Washington, DC |
Verlag | AAAI Press |
Seiten | 5524-5531 |
Seitenumfang | 8 |
ISBN (elektronisch) | 9781577358800 |
DOIs | |
Publikationsstatus | Veröffentlicht - 27 Juni 2023 |
Extern publiziert | Ja |
Veranstaltung | 37th AAAI Conference on Artificial Intelligence, AAAI 2023 - Washington, USA/Vereinigte Staaten Dauer: 7 Feb. 2023 → 14 Feb. 2023 |
Publikationsreihe
Reihe | Proceedings of the AAAI Conference on Artificial Intelligence |
---|---|
Nummer | 5 |
Band | 37 |
ISSN | 2159-5399 |
Konferenz
Konferenz | 37th AAAI Conference on Artificial Intelligence, AAAI 2023 |
---|---|
Land/Gebiet | USA/Vereinigte Staaten |
Ort | Washington |
Zeitraum | 7/02/23 → 14/02/23 |
Bibliographische Notiz
Publisher Copyright:Copyright © 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.