Voting-based group formation

Piotr Faliszewski; Arkadii Slinko; Nimrod Talmon

Voting-based group formation

Piotr Faliszewski, Arkadii Slinko, Nimrod Talmon

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

We study a combinatorial problem formulated in terms of the following group-formation scenario. Given some agents, where each agent has preferences over the set of potential group leaders, the task is to partition the agents into groups and assign a group leader to each of them, so that the group leaders have as high support as possible from the groups they are assigned to lead. We model this scenario as a voting problem, where the goal is to partition a set of voters into a prescribed number of groups so that each group elects its leader, i.e., their leader is a unique winner in the corresponding election. We study the computational complexity of this problem (and several of its variants) for Approval elections.

Original language	English
Pages (from-to)	243-249
Number of pages	7
Journal	IJCAI International Joint Conference on Artificial Intelligence
Volume	2016-January
State	Published - 1 Jan 2016
Externally published	Yes
Event	25th International Joint Conference on Artificial Intelligence, IJCAI 2016 - New York, United States Duration: 9 Jul 2016 → 15 Jul 2016

ASJC Scopus subject areas

Artificial Intelligence

Cite this

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title = "Voting-based group formation",

abstract = "We study a combinatorial problem formulated in terms of the following group-formation scenario. Given some agents, where each agent has preferences over the set of potential group leaders, the task is to partition the agents into groups and assign a group leader to each of them, so that the group leaders have as high support as possible from the groups they are assigned to lead. We model this scenario as a voting problem, where the goal is to partition a set of voters into a prescribed number of groups so that each group elects its leader, i.e., their leader is a unique winner in the corresponding election. We study the computational complexity of this problem (and several of its variants) for Approval elections.",

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AU - Slinko, Arkadii

AU - Talmon, Nimrod

N1 - Funding Information: Piotr Faliszewski was supported NCN grant DEC-2012/06/M/ST1/00358. Arkadii Slinko was supported by the Royal Society of NZ Marsden Fund UOA-254. Nimrod Talmon was supported by a postdoctoral fellowship from I-CORE ALGO

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N2 - We study a combinatorial problem formulated in terms of the following group-formation scenario. Given some agents, where each agent has preferences over the set of potential group leaders, the task is to partition the agents into groups and assign a group leader to each of them, so that the group leaders have as high support as possible from the groups they are assigned to lead. We model this scenario as a voting problem, where the goal is to partition a set of voters into a prescribed number of groups so that each group elects its leader, i.e., their leader is a unique winner in the corresponding election. We study the computational complexity of this problem (and several of its variants) for Approval elections.

AB - We study a combinatorial problem formulated in terms of the following group-formation scenario. Given some agents, where each agent has preferences over the set of potential group leaders, the task is to partition the agents into groups and assign a group leader to each of them, so that the group leaders have as high support as possible from the groups they are assigned to lead. We model this scenario as a voting problem, where the goal is to partition a set of voters into a prescribed number of groups so that each group elects its leader, i.e., their leader is a unique winner in the corresponding election. We study the computational complexity of this problem (and several of its variants) for Approval elections.

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M3 - Conference article

AN - SCOPUS:85006132467

SN - 1045-0823

VL - 2016-January

SP - 243

EP - 249

JO - IJCAI International Joint Conference on Artificial Intelligence

JF - IJCAI International Joint Conference on Artificial Intelligence

T2 - 25th International Joint Conference on Artificial Intelligence, IJCAI 2016

Y2 - 9 July 2016 through 15 July 2016

ER -

Voting-based group formation

Abstract

ASJC Scopus subject areas

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