Publication | Open Access
Junta Distributions and the Average-Case Complexity of Manipulating Elections
153
Citations
18
References
2007
Year
Computational Social ChoiceAverage CaseGame TheoryComputational ComplexityPolitical BehaviorSmart VotingSocial SciencesDemocracyAlgorithmic Mechanism DesignElectronic VotingComplexity MeasureElection ForecastingMechanism DesignElectionsJunta DistributionsVoting RuleComputer SciencePolitical CompetitionBusinessPolitical Science
Encouraging voters to truthfully reveal their preferences in an election has long been an important issue. Recently, computational complexity has been suggested as a means of precluding strategic behavior. Previous studies have shown that some voting protocols are hard to manipulate, but used NP-hardness as the complexity measure. Such a worst-case analysis may be an insufficient guarantee of resistance to manipulation. Indeed, we demonstrate that NP-hard manipulations may be tractable in the average case. For this purpose, we augment the existing theory of average-case complexity with some new concepts. In particular, we consider elections distributed with respect to junta distributions, which concentrate on hard instances. We use our techniques to prove that scoring protocols are susceptible to manipulation by coalitions, when the number of candidates is constant.
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