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 language | English (US) |
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Pages | 359-366 |
Number of pages | 8 |
State | Published - 2013 |
Event | 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States Duration: May 6 2013 → May 10 2013 |
Other
Other | 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 |
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Country/Territory | United States |
City | Saint Paul, MN |
Period | 5/6/13 → 5/10/13 |
Keywords
- Multi-winner elections
- Tie-breaking rules
- Voting
ASJC Scopus subject areas
- Artificial Intelligence