Vote elicitation: complexity and strategy-proofness
Eighteenth national conference on Artificial intelligence
Generalizing preference elicitation in combinatorial auctions
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Communication complexity of common voting rules
Proceedings of the 6th ACM conference on Electronic commerce
The Computer Journal
Complexity of terminating preference elicitation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Privacy-Preserving Collaborative E-Voting
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Aggregating Partially Ordered Preferences
Journal of Logic and Computation
Uncertainty in preference elicitation and aggregation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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
Winner determination in sequential majority voting
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Incompleteness and incomparability in preference aggregation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Dealing with incomplete preferences in soft constraint problems
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Vote elicitation with probabilistic preference models: empirical estimation and cost tradeoffs
ADT'11 Proceedings of the Second international conference on Algorithmic decision theory
Optimal social choice functions: a utilitarian view
Proceedings of the 13th ACM Conference on Electronic Commerce
Robust approximation and incremental elicitation in voting protocols
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Campaigns for lazy voters: truncated ballots
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Possible and necessary winners of partial tournaments
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Communication complexity of approximating voting rules
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Multi-winner social choice with incomplete preferences
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Efficient vote elicitation under candidate uncertainty
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Voting is an essential mechanism that allows multiple agents to reach a joint decision. The joint decision, representing a function over the preferences of all agents, is the winner among all possible (candidate) decisions. To compute the winning candidate, previous work has typically assumed that voters send their complete set of preferences for computation, and in fact this has been shown to be required in the worst case. However, in practice, it may be infeasible for all agents to send a complete set of preferences due to communication limitations and willingness to keep as much information private as possible. The goal of this paper is to empirically evaluate algorithms to reduce communication on various sets of experiments. Accordingly, we propose an iterative algorithm that allows the agents to send only part of their preferences, incrementally. Experiments with simulated and real-world data show that this algorithm results in an average of 35% savings in communications, while guaranteeing that the actual winning candidate is revealed. A second algorithm applies a greedy heuristic to save up to 90% of communications. While this heuristic algorithm cannot guarantee that a true winning candidate is found, we show that in practice, close approximations are obtained.