An automated meeting scheduling system that utilizes user preferences
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Voting for movies: the anatomy of a recommender system
Proceedings of the third annual conference on Autonomous Agents
A heuristic technique for multi-agent planning
Annals of Mathematics and Artificial Intelligence
Complexity of manipulating elections with few candidates
Eighteenth national conference on Artificial intelligence
Automated design of scoring rules by learning from examples
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Copeland Voting Fully Resists Constructive Control
AAIM '08 Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management
Llull and copeland voting broadly resist bribery and control
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Llull and Copeland voting computationally resist bribery and constructive control
Journal of Artificial Intelligence Research
The Effects of Noise and Manipulation on the Accuracy of Collective Decision Rules
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
Manipulation of copeland elections
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Voting almost maximizes social welfare despite limited communication
Artificial Intelligence
On elections with robust winners
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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In an election held in a noisy environment, agents may unintentionally perturb the outcome by communicating faulty preferences. We investigate this setting by introducing a theoretical model of noisy preference aggregation and formally defining the (worst-case) robustness of a voting rule. We use our model to analytically bound the robustness of various prominent rules. The results show that the robustness of voting rules is diverse, with different rules positioned at either end of the spectrum. These results allow selection of voting rules that support preference aggregation in the face of noise.