Conference item
Multiwinner candidacy games
- Abstract:
- In strategic candidacy games, both voters and candidates have preferences over the set of possible election outcomes, and candidates may strategically withdraw from the election in order to manipulate the result in their favor. In this work, we extend the candidacy game model to the setting of multiwinner elections, where the goal is to select a fixed-size committee of candidates, rather than a single winner. We examine the existence and properties of Nash equilibria in the resulting class of games, under various voting rules and voter preference structures.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.2MB, Terms of use)
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- Publication website:
- https://dl.acm.org/doi/abs/10.5555/3398761.3398873
Authors
- Publisher:
- International Foundation for Autonomous Agents and Multiagent Systems
- Host title:
- AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems
- Pages:
- 957-965
- Publication date:
- 2020-05-05
- Acceptance date:
- 2020-01-15
- Event title:
- 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020)
- Event location:
- Auckland, New Zealand
- Event website:
- https://aamas2020.conference.auckland.ac.nz/
- Event start date:
- 2020-05-09
- Event end date:
- 2020-05-13
- EISSN:
-
1558-2914
- ISSN:
-
1548-8403
- ISBN:
- 9781450375184
- Language:
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English
- Keywords:
- Pubs id:
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1148905
- Local pid:
-
pubs:1148905
- Deposit date:
-
2021-04-19
- ARK identifier:
Terms of use
- Copyright holder:
- International Foundation for Autonomous Agents and Multiagent Systems
- Copyright date:
- 2020
- Rights statement:
- © 2020 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
- Notes:
- This paper was presented at the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), 9–13 May 2020, Auckland, New Zealand. This is the publisher's version of the paper. The final version is available online from the International Foundation for Autonomous Agents and Multiagent Systems at: https://dl.acm.org/doi/abs/10.5555/3398761.3398873
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