Iterative Goal-Based Approval Voting

Leyla Ade and Arianna Novaro (arianna.novaro@univ-paris1.fr)
Additional contact information
Leyla Ade: Institut für Philosphie, Universität Bayreuth [Bayreuth, Germany] - Universität Bayreuth [Deutschland] = University of Bayreuth [Germany] = Université de Bayreuth [Allemagne]
Arianna Novaro: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

Post-Print from HAL

Abstract: In iterative voting, a group of agents who has to take a collective decision has the possibility to individually and sequentially alter their vote, to improve the outcome for themselves. In this paper, we extend with an iterative component the recent framework of goal-based voting, where agents submit compactly expressed individual goals. For the aggregation, we focus on an adaptation of the classical Approval rule to this setting, and we model agents having optimistic or pessimistic satisfaction functions based on the Hamming distance. The results of our analysis are twofold: first, we provide conditions under which the application of the Approval rule is guaranteed to converge to a stable outcome; second, we study the quality of the social welfare yielded by the iteration process.

Date: 2022-09-14
References: Add references at CitEc
Citations:

Published in Multi-Agent Systems,19th European Conference, EUMAS 2022, Düsseldorf, Germany, September 14–16, 2022, Proceedings, Sep 2022, Düsseldorf, Germany. pp.3-21, ⟨10.1007/978-3-031-20614-6_1⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04085360

DOI: 10.1007/978-3-031-20614-6_1

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).