On manipulation in multi-winner elections based on scoring rules

Svetlana Obraztsova, Yair Zick, Edith Elkind

Research output: Contribution to conferencePaperpeer-review

19 Scopus citations

Abstract

Multi-winner elections model scenarios where voters must select a fixed-size group of candidates based on their individual preferences. In such scenarios, it is often the case that voters are incentivized to manipulate, i.e. misreport their preferences in order to obtain a better outcome. In this paper, we study the complexity of manipulating multi-winner elections under scoring rules, with a particular focus on the role of tie-breaking rules. We consider both lexicographic tie-breaking rules, which break ties according to a fixed ordering of the candidates, and a natural randomized tie-breaking rule. We describe polynomial-time manipulation algorithms for several special cases of our problem. Specifically, we show that finding a successful manipulation is easy if the underlying voting rule is k-Approval or the number of candidates to be elected is bounded by a constant (for both types of tie-breaking rules), as well as if the manipulator's utility function only takes values in {0,1} and the ties are broken in the manipulator's favor.

Original languageEnglish (US)
Pages359-366
Number of pages8
StatePublished - 2013
Event12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States
Duration: May 6 2013May 10 2013

Other

Other12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013
Country/TerritoryUnited States
CitySaint Paul, MN
Period5/6/135/10/13

Keywords

  • Multi-winner elections
  • Tie-breaking rules
  • Voting

ASJC Scopus subject areas

  • Artificial Intelligence

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