When are elections with few candidates hard to manipulate?
Journal of the ACM (JACM)
Anyone but him: The complexity of precluding an alternative
Artificial Intelligence
On the complexity of manipulating elections
CATS '07 Proceedings of the thirteenth Australasian symposium on Theory of computing - Volume 65
Algorithms for the coalitional manipulation problem
Artificial Intelligence
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Where are the really hard manipulation problems? the phase transition in manipulating the veto rule
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Using complexity to protect elections
Communications of the ACM
An Empirical Study of the Manipulability of Single Transferable Voting
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Control complexity in fallback voting
CATS '10 Proceedings of the Sixteenth Symposium on Computing: the Australasian Theory - Volume 109
Information and Computation
The complexity of voter partition in Bucklin and fallback voting: solving three open problems
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
How hard is it to control an election?
Mathematical and Computer Modelling: An International Journal
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Annals of Mathematics and Artificial Intelligence
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Walsh [23,22], Davies et al. [9], and Narodytska et al. [20] studied various voting systems empirically and showed that they can often be manipulated effectively, despite their manipulation problems being NP-hard. Such an experimental approach is sorely missing for NP-hard control problems, where control refers to attempts to tamper with the outcome of elections by adding/delet-ing/partitioning either voters or candidates. We experimentally tackle NP-hard control problems for Bucklin and fallback voting, which among natural voting systems with efficient winner determination are the systems currently known to display the broadest resistance to control in terms of NP-hardness [12,11]. We also investigate control resistance experimentally for plurality voting, one of the first voting systems analyzed with respect to electoral control [1,18]. Our findings indicate that NP-hard control problems can often be solved effectively in practice. Moreover, our experiments allow a more fine-grained analysis and comparison--across various control scenarios, vote distribution models, and voting systems--than merely stating NP-hardness for all these control problems.