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The Possible-Winner problem asks, given an election where the voters' preferences over the set of candidates is partially specified, whether a distinguished candidate can become a winner. In this work, we consider the computational…

计算机科学与博弈论 · 计算机科学 2018-02-27 Batya Kenig

In multiwinner approval elections with many candidates, voters may struggle to determine their preferences over the entire slate of candidates. It is therefore of interest to explore which (if any) fairness guarantees can be provided under…

计算机科学与博弈论 · 计算机科学 2025-10-14 Drew Springham , Edith Elkind , Bart de Keijzer , Maria Polukarov

We introduce a single-winner perspective on voting on matchings, in which voters have preferences over possible matchings in a graph, and the goal is to select a single collectively desirable matching. Unlike in classical matching problems,…

计算机科学与博弈论 · 计算机科学 2026-01-28 Niclas Boehmer , Jessica Dierking

We consider election scenarios with incomplete information, a situation that arises often in practice. There are several models of incomplete information and accordingly, different notions of outcomes of such elections. In one well-studied…

计算机科学与博弈论 · 计算机科学 2016-10-27 Palash Dey , Neeldhara Misra

Predicting the winner of an election is a favorite problem both for news media pundits and computational social choice theorists. Since it is often infeasible to elicit the preferences of all the voters in a typical prediction scenario, a…

数据结构与算法 · 计算机科学 2016-04-21 Arnab Bhattacharyya , Palash Dey

We consider the problem of predicting winners in elections, for the case where we are given complete knowledge about all possible candidates, all possible voters (together with their preferences), but where it is uncertain either which…

计算机科学与博弈论 · 计算机科学 2016-03-27 Krzysztof Wojtas , Krzysztof Magiera , Tomasz Miąsko , Piotr Faliszewski

We consider a setting where an agent's uncertainty is represented by a set of probability measures, rather than a single measure. Measure-by-measure updating of such a set of measures upon acquiring new information is well-known to suffer…

计算机科学与博弈论 · 计算机科学 2016-11-04 Joseph Y. Halpern , Samantha Leung

We consider multi-agent systems where agents' preferences are aggregated via sequential majority voting: each decision is taken by performing a sequence of pairwise comparisons where each comparison is a weighted majority vote among the…

人工智能 · 计算机科学 2012-04-18 Maria Pini , Francesca Rossi , Brent Venable , Toby Walsh

We consider the approval-based model of elections, and undertake a computational study of voting rules which select committees whose size is not predetermined. While voting rules that output committees with a predetermined number of winning…

计算机科学与博弈论 · 计算机科学 2017-11-20 Piotr Faliszewski , Arkadii Slinko , Nimrod Talmon

Multi-winner voting is the process of selecting a fixed-size set of representative candidates based on voters' preferences. It occurs in applications ranging from politics (parliamentary elections) to the design of modern computer…

计算机科学与博弈论 · 计算机科学 2022-11-22 Martin Lackner , Piotr Skowron

Various voting rules are based on ranking the candidates by scores induced by aggregating voter preferences. A winner (respectively, unique winner) is a candidate who receives a score not smaller than (respectively, strictly greater than)…

计算机科学与博弈论 · 计算机科学 2021-02-01 Aviram Imber , Benny Kimelfeld

We consider a setting where an agent's uncertainty is represented by a set of probability measures, rather than a single measure. Measure-bymeasure updating of such a set of measures upon acquiring new information is well-known to suffer…

计算机科学与博弈论 · 计算机科学 2013-02-26 Joseph Y. Halpern , Samantha Leung

When voter preferences are known in an incomplete (partial) manner, winner determination is commonly treated as the identification of the necessary and possible winners; these are the candidates who win in all completions or at least one…

计算机科学与博弈论 · 计算机科学 2020-02-24 Aviram Imber , Benny Kimelfeld

Determining how close a winner of an election is to becoming a loser, or distinguishing between different possible winners of an election, are major problems in computational social choice. We tackle these problems for so-called weighted…

计算机科学与博弈论 · 计算机科学 2024-08-14 Michelle Döring , Jannik Peters

We study the complexity of (approximate) winner determination under the Monroe and Chamberlin--Courant multiwinner voting rules, which determine the set of representatives by optimizing the total (dis)satisfaction of the voters with their…

人工智能 · 计算机科学 2013-12-17 Piotr Skowron , Piotr Faliszewski , Arkadii Slinko

In approval-based multiwinner voting, voters express approval preferences over a set of candidates, and the goal is to return a winning committee. This model captures a broad range of subset selection problems under preferences. Prior work…

计算机科学与博弈论 · 计算机科学 2026-04-28 Niclas Boehmer , Luca Kreisel , Jannik Peters

Several election districts in the US have recently moved to ranked-choice voting (RCV) to decide the results of local elections. RCV allows voters to rank their choices, and the results are computed in rounds, eliminating one candidate at a…

计算机与社会 · 计算机科学 2022-06-28 Alborz Jelvani , Amélie Marian

Tournament solutions are frequently used to select winners from a set of alternatives based on pairwise comparisons between alternatives. Prior work has shown that several common tournament solutions tend to select large winner sets and…

计算机科学与博弈论 · 计算机科学 2021-09-30 Markus Brill , Ulrike Schmidt-Kraepelin , Warut Suksompong

The Possible Winner (PW) problem, a fundamental algorithmic problem in computational social choice, concerns elections where voters express only partial preferences between candidates. Via a sequence of investigations, a complete…

计算机科学与博弈论 · 计算机科学 2020-03-26 Vishal Chakraborty , Phokion G. Kolaitis

Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters. However, if candidates have sensitive attributes such as gender or ethnicity (when selecting…

计算机与社会 · 计算机科学 2018-06-20 L. Elisa Celis , Lingxiao Huang , Nisheeth K. Vishnoi
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