TY - JOUR
T1 - Elections with few voters
T2 - Candidate control can be easy
AU - Chen, Jiehua
AU - Faliszewski, Piotr
AU - Niedermeier, Rolf
AU - Talmon, Nimrod
N1 - Publisher Copyright: © 2017 AI Access Foundation. All rights reserved.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - We study the computational complexity of candidate control in elections with few voters, that is, we consider the parameterized complexity of candidate control in elections with respect to the number of voters as a parameter. We consider both the standard scenario of adding and deleting candidates, where one asks whether a given candidate can become a winner (or, in the destructive case, can be precluded from winning) by adding or deleting few candidates, as well as a combinatorial scenario where adding/deleting a candidate automatically means adding or deleting a whole group of candidates. Considering several fundamental voting rules, our results show that the parameterized complexity of candidate control, with the number of voters as the parameter, is much more varied than in the setting with many voters.
AB - We study the computational complexity of candidate control in elections with few voters, that is, we consider the parameterized complexity of candidate control in elections with respect to the number of voters as a parameter. We consider both the standard scenario of adding and deleting candidates, where one asks whether a given candidate can become a winner (or, in the destructive case, can be precluded from winning) by adding or deleting few candidates, as well as a combinatorial scenario where adding/deleting a candidate automatically means adding or deleting a whole group of candidates. Considering several fundamental voting rules, our results show that the parameterized complexity of candidate control, with the number of voters as the parameter, is much more varied than in the setting with many voters.
UR - http://www.scopus.com/inward/record.url?scp=85040689828&partnerID=8YFLogxK
U2 - https://doi.org/10.1613/jair.5515
DO - https://doi.org/10.1613/jair.5515
M3 - Article
SN - 1076-9757
VL - 60
SP - 937
EP - 1002
JO - Journal Of Artificial Intelligence Research
JF - Journal Of Artificial Intelligence Research
ER -