TY - JOUR
T1 - Junta distributions and the average-case complexity of manipulating elections
AU - Procaccia, Ariel D.
AU - Rosenschein, Jeffrey S.
PY - 2007
Y1 - 2007
N2 - 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 MP-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.
AB - 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 MP-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.
UR - http://www.scopus.com/inward/record.url?scp=34249029918&partnerID=8YFLogxK
U2 - 10.1613/jair.2148
DO - 10.1613/jair.2148
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AN - SCOPUS:34249029918
SN - 1076-9757
VL - 28
SP - 157
EP - 181
JO - Journal of Artificial Intelligence Research
JF - Journal of Artificial Intelligence Research
ER -