TY - GEN
T1 - Selecting voting locations for fun and profit
AU - Fitzsimmons, Zack
AU - Lev, Omer
N1 - Publisher Copyright:
© 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - While manipulative attacks on elections have been well-studied, only recently has attention turned to attacks that account for geographic information, which are extremely common in the real world. The most well known in the media is gerrymandering, in which district border-lines are changed to increase a party's chance to win, but a different geographical manipulation involves influencing the election by selecting the location of polling places, as many people are not willing to go to any distance to vote. In this paper we initiate the study of this manipulation. We find that while it is easy to manipulate the selection of polling places on the line, it becomes difficult already on the plane or in the case of more than two candidates. Moreover, we show that for more than two candidates the problem is inapproximable. However, we find a few restricted cases on the plane where some algorithms perform well. Finally, we discuss how existing results for standard control actions hold in the geographic setting, consider additional control actions in the geographic setting, and suggest directions for future study.
AB - While manipulative attacks on elections have been well-studied, only recently has attention turned to attacks that account for geographic information, which are extremely common in the real world. The most well known in the media is gerrymandering, in which district border-lines are changed to increase a party's chance to win, but a different geographical manipulation involves influencing the election by selecting the location of polling places, as many people are not willing to go to any distance to vote. In this paper we initiate the study of this manipulation. We find that while it is easy to manipulate the selection of polling places on the line, it becomes difficult already on the plane or in the case of more than two candidates. Moreover, we show that for more than two candidates the problem is inapproximable. However, we find a few restricted cases on the plane where some algorithms perform well. Finally, we discuss how existing results for standard control actions hold in the geographic setting, consider additional control actions in the geographic setting, and suggest directions for future study.
UR - http://www.scopus.com/inward/record.url?scp=85097334764&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85097334764
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 224
EP - 230
BT - Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020
A2 - Bessiere, Christian
PB - International Joint Conferences on Artificial Intelligence
T2 - 29th International Joint Conference on Artificial Intelligence, IJCAI 2020
Y2 - 1 January 2021
ER -