Average case complete problems
SIAM Journal on Computing
More complicated questions about maxima and minima, and some closures of NP
Theoretical Computer Science
The Boolean hierarchy I: structural properties
SIAM Journal on Computing
The polynomial time hierarchy collapses if the Boolean hierarchy collapses
SIAM Journal on Computing
SIAM Journal on Computing
Approximate solution of NP optimization problems
Theoretical Computer Science
A tight analysis of the greedy algorithm for set cover
Journal of Algorithms
Average-case computational complexity theory
Complexity theory retrospective II
Canonical Coin Changing and Greedy Solutions
Journal of the ACM (JACM)
A probabilistic analysis of a greedy algorithm arising from computational biology
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Introduction to Algorithms
Two remarks on the power of counting
Proceedings of the 6th GI-Conference on Theoretical Computer Science
A New Probabilistic Model for the Study of Algorithmic Properties of Random Graph Problems
Proceedings of the 1983 International FCT-Conference on Fundamentals of Computation Theory
The Probabilistic Analysis of a Greedy Satisfiability Algorithm
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
On finding the exact solution of a zero-one knapsack problem
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
A personal view of average-case complexity
SCT '95 Proceedings of the 10th Annual Structure in Complexity Theory Conference (SCT'95)
Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time
Journal of the ACM (JACM)
The complexity of Kemeny elections
Theoretical Computer Science
On Worst-Case to Average-Case Reductions for NP Problems
SIAM Journal on Computing
Nonexistence of voting rules that are usually hard to manipulate
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
The complexity of bribery in elections
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Llull and copeland voting broadly resist bribery and control
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Junta distributions and the average-case complexity of manipulating elections
Journal of Artificial Intelligence Research
Guarantees for the success frequency of an algorithm for finding dodgson-election winners
MFCS'06 Proceedings of the 31st international conference on Mathematical Foundations of Computer Science
Copeland Voting Fully Resists Constructive Control
AAIM '08 Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management
Parameterized Computational Complexity of Dodgson and Young Elections
SWAT '08 Proceedings of the 11th Scandinavian workshop on Algorithm Theory
Frequency of correctness versus average polynomial time
Information Processing Letters
Note: Generalized juntas and NP-hard sets
Theoretical Computer Science
Llull and Copeland voting computationally resist bribery and constructive control
Journal of Artificial Intelligence Research
How hard is bribery in elections?
Journal of Artificial Intelligence Research
Socially desirable approximations for Dodgson's voting rule
Proceedings of the 11th ACM conference on Electronic commerce
Using complexity to protect elections
Communications of the ACM
Multimode control attacks on elections
Journal of Artificial Intelligence Research
Bribery in path-disruption games
ADT'11 Proceedings of the Second international conference on Algorithmic decision theory
On the approximability of Dodgson and Young elections
Artificial Intelligence
Socially desirable approximations for dodgson’s voting rule
ACM Transactions on Algorithms (TALG)
Annals of Mathematics and Artificial Intelligence
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In the year 1876 the mathematician Charles Dodgson, who wrote fiction under the now more famous name of Lewis Carroll, devised a beautiful voting system that has long fascinated political scientists. However, determining the winner of a Dodgson election is known to be complete for the Θ2 p level of the polynomial hierarchy. This implies that unless P=NP no polynomial-time solution to this problem exists, and unless the polynomial hierarchy collapses to NP the problem is not even in NP. Nonetheless, we prove that when the number of voters is much greater than the number of candidates—although the number of voters may still be polynomial in the number of candidates—a simple greedy algorithm very frequently finds the Dodgson winners in such a way that it “knows” that it has found them, and furthermore the algorithm never incorrectly declares a nonwinner to be a winner.