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Phragmen's Voting Methods and Justified Representation
Univ Oxford, Oxford, England.
Duke Univ, Durham, NC 27706 USA.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Analysis and Probability Theory.
Univ Oxford, Oxford, England.
2017 (English)In: Thirty-First AAAI Conference On Artificial Intelligence, Assoc Advancement Artificial Intelligence , 2017, p. 406-413Conference paper, Published paper (Refereed)
Abstract [en]

In the late 19th century, Lars Edvard Phragmen proposed a load-balancing approach for selecting committees based on approval ballots. We consider three committee voting rules resulting from this approach: two optimization variants-one minimizing the maximal load and one minimizing the variance of loads-and a sequential variant. We study Phragmen's methods from an axiomatic point of view, focussing on justified representation and related properties that have recently been introduced by Aziz et al. (2015a) and Sanchez-Fernandez et al. (2017). We show that the sequential variant satisfies proportional justified representation, making it the first known polynomial-time computable method with this property. Moreover, we show that the optimization variants satisfy perfect representation. We also analyze the computational complexity of Phragmen's methods and provide mixed- integer programming based algorithms for computing them.

Place, publisher, year, edition, pages
Assoc Advancement Artificial Intelligence , 2017. p. 406-413
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-399797ISI: 000485630700057OAI: oai:DiVA.org:uu-399797DiVA, id: diva2:1379450
Conference
31st AAAI Conference on Artificial Intelligence, San Francisco, CA, Feb 04-09, 2017
Funder
Knut and Alice Wallenberg FoundationAvailable from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-17Bibliographically approved

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