Voting for movies: the anatomy of a recommender system
Proceedings of the third annual conference on Autonomous Agents
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
The complexity theory companion
The complexity theory companion
A heuristic technique for multi-agent planning
Annals of Mathematics and Artificial Intelligence
Some connections between nonuniform and uniform complexity classes
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
The complexity of Kemeny elections
Theoretical Computer Science
When are elections with few candidates hard to manipulate?
Journal of the ACM (JACM)
Parameterized Computational Complexity of Dodgson and Young Elections
SWAT '08 Proceedings of the 11th Scandinavian workshop on Algorithm Theory
On the approximability of Dodgson and Young elections
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
On distance rationalizability of some voting rules
Proceedings of the 12th Conference on Theoretical Aspects of Rationality and Knowledge
Determining possible and necessary winners under common voting rules given partial orders
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Complexity of strategic behavior in multi-winner elections
Journal of Artificial Intelligence Research
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
A multivariate complexity analysis of determining possible winners given incomplete votes
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Preference functions that score rankings and maximum likelihood estimation
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
The complexity of manipulative attacks in nearly single-peaked electorates
Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge
Multimode control attacks on elections
Journal of Artificial Intelligence Research
Homogeneity and monotonicity of distance-rationalizable voting rules
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
On the approximability of Dodgson and Young elections
Artificial Intelligence
Aggregating dependency graphs into voting agendas in multi-issue elections
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Strategyproof approximations of distance rationalizable voting rules
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Studies in computational aspects of voting: open problems of downey and fellows
The Multivariate Algorithmic Revolution and Beyond
When do noisy votes reveal the truth?
Proceedings of the fourteenth ACM conference on Electronic commerce
On swap-distance geometry of voting rules
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
The complexity of manipulative attacks in nearly single-peaked electorates
Artificial Intelligence
On the computation of fully proportional representation
Journal of Artificial Intelligence Research
Approximately classic judgement aggregation
Annals of Mathematics and Artificial Intelligence
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A voting rule is an algorithm for determining the winner in an election, and there are several approaches that have been used to justify the proposed rules. One justification is to show that a rule satisfies a set of desirable axioms that uniquely identify it. Another is to show that the calculation that it performs is actually maximum likelihood estimation relative to a certain model of noise that affects voters (MLE approach). The third approach, which has been recently actively investigated, is the so-called distance rationalizability framework. In it, a voting rule is defined via a class of consensus elections (i.e., a class of elections that have a clear winner) and a distance function. A candidate c is a winner of an election E if c wins in one of the consensus elections that are closest to E relative to the given distance. In this paper, we show that essentially any voting rule is distance-rationalizable if we do not restrict the two ingredients of the rule: the consensus class and the distance. Thus distance rationalizability of a rule does not by itself guarantee that the voting rule has any desirable properties. However, we demonstrate that the distance used to rationalize a given rule may provide useful information about this rule's behavior. Specifically, we identify a large class of distances, which we call votewise distances, and show that if a rule is rationalized via a distance from this class, many important properties of this rule can be easily expressed in terms of the underlying distance. This enables us to provide a new characterization of scoring rules and to establish a connection with the MLE framework. We also give bounds on the complexity of the winner determination problem for distance-rationalizable rules.