Abstract
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.
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Blosser, G., & Zhan, J. (2008). Privacy-preserving collaborative e-voting. In Intelligence and security informatics (pp. 508–513). Berlin, Heidelberg: Springer.
Conitzer, V., & Sandholm, T. (2002). Vote elicitation: Complexity and strategy-proofness. In Eighteenth national conference on artificial intelligence, pp. 392–397.
Conitzer, V., & Sandholm, T. (2005). Communication complexity of common voting rules. In EC ’05: Proceedings of the 6th ACM conference on electronic commerce, pp. 78–87.
Faltings B., Macho-Gonzalez S. (2005) Open constraint programming. Artifitial Intelligence 161(1–2): 181–208
Gelain, M., Pini, M. S., Rossi, F., & Venable, K. B. (2007) Dealing with incomplete preferences in soft constraint problems. In The 13th international conference on principles and practice of constraint prgramming (CP-07), pp. 286–300.
Hudson, B., & Sandholm, T. (2003). Generalizing preference elicitation in combinatorial auctions. In Proceedings of the second international joint conference on autonomous agents and multiagent systems (AAMAS), pp. 1014–1015.
Konczak, K. (2006). Voting theory in answer set programming. In The 20th workshop on logic programming (WLP-06), pp. 45–53.
Konczak, K., & Lang, J. (2005). Voting procedures with incomplete preferences. In Proceedings of multidisciplinary IJCAI’05 workshop on advances in preference handling, Edinburg, Scotland.
Lang, J., Pini, M. S., Rossi, F., Venable, K. B., & Walsh, T. (2007). Winner determination in sequential majority voting. In Proceedings of the international joint conference on artificial intelligence (IJCAI), pp. 1372–1377.
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Pini, M. S., Rossi, F., Venable, K. B., & Walsh, T. (2007). Incompleteness and incomparability in preference aggregation. In M. M. Veloso (Ed.), In Proceedings of the international joint conference on artificial intelligence (IJCAI), pp. 1464–1469.
Pini M. S., Rossi F., Venable K. B., Walsh T. (2009) Aggregating partially ordered preferences. Journal of Logic and Computation 19(3): 475–502
Pitt J., Kamara L., Sergot M., Artikis A. (2006) Voting in multi-agent systems. Computer Journal 49(2): 156–170
Tambe, M., Bowring, E., Pearce, J. P., Varakantham, P., Scerri, P., & Pynadath, D. V. (2006). Electric elves: What went wrong and why. In Proceedings of the AAAI spring symposium on what went wrong and why: Lessons from AI research and applications.
Walsh, T. (2007). Uncertainty in preference elicitation and aggregation. In Proceedings of the 22nd national conference on Artificial intelligence (AAAI-07), pp. 3–8.
Walsh, T. (2008). Complexity of terminating preference elicitation. In Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems (AAMAS), pp. 967–974.
Xia, L., & Conitzer, V. (2008) Determining possible and necessary winners under common voting rules given partial orders. In Proceedings of the 23rd national conference on artificial intelligence (AAAI-08), pp. 196–201.
Zhan J., Matwin S., Chang L.-W. (2004) Privacy-preserving electronic voting. Information & Security: An International Journal 15(2): 165–180
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Kalech, M., Kraus, S., Kaminka, G.A. et al. Practical voting rules with partial information. Auton Agent Multi-Agent Syst 22, 151–182 (2011). https://doi.org/10.1007/s10458-010-9133-6
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DOI: https://doi.org/10.1007/s10458-010-9133-6