Szczegóły publikacji
Opis bibliograficzny
The price of justified representation / Edith Elkind, Piotr FALISZEWSKI, Ayumi Igarashi, Pasin Manurangsi, Ulrike Schmidt-Kraepelin, Warut Suksompong // W: AAAI-22 / IAAI-22 / EAAI-22 proceedings : thirty-sixth AAAI Conference on Artificial Intelligence; thirty-fourth Conference on Innovative Applications of Artificial Intelligence; the twelveth Symposium on Educational Advances in Artificial Intelligence : February 22 – March 1, 2022, held virtually, Palo Alto, California, USA. — Palo Alto : AAAI Press, cop. 2022. — (Proceedings of the ... AAAI Conference on Artificial Intelligence ; ISSN 2159-5399 ; Vol. 36 No. 5: AAAI-22 Technical Tracks 5 ). — ISBN - wspólny dla 11 vol. — ISBN: 978-1-57735-876-3; ISBN: 1-57735-876-7. — S. 4983–4990. — Bibliogr. s. 4990, Abstr.
Autorzy (6)
- Elkind Edith
- AGHFaliszewski Piotr
- Igarashi Ayumi
- Manurangsi Pasin
- Schmidt-Kraepelin Ulrike
- Suksompong Warut
Dane bibliometryczne
| ID BaDAP | 142804 |
|---|---|
| Data dodania do BaDAP | 2022-10-10 |
| DOI | 10.1609/aaai.v36i5.20429 |
| Rok publikacji | 2022 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencje | National Conference of the American Association for Artificial Intelligence 2022, Innovative Applications in AI 2022 |
| Czasopismo/seria | Proceedings of the ... AAAI Conference on Artificial Intelligence |
Abstract
In multiwinner approval voting, the goal is to select k-member committees based on voters' approval ballots. A well-studied concept of proportionality in this context is the justified representation (JR) axiom, which demands that no large cohesive group of voters remains unrepresented. However, the JR axiom may conflict with other desiderata, such as coverage (maximizing the number of voters who approve at least one committee member) or social welfare (maximizing the number of approvals obtained by committee members). In this work, we investigate the impact of imposing the JR axiom (as well as the more demanding EJR axiom) on social welfare and coverage. Our approach is threefold: we derive worst-case bounds on the loss of welfare/coverage that is caused by imposing JR, study the computational complexity of finding 'good' committees that provide JR (obtaining a hardness result, an approximation algorithm, and an exact algorithm for one-dimensional preferences), and examine this setting empirically on several synthetic datasets.
