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Possible and Necessary Winners of Partial Tournaments

by Haris Aziz, Paul Harrenstein, Markus Brill, Jérôme Lang, Felix Fischer, Hans Georg Seedig
"... We study the problem of computing possible and necessary winners for partially specified weighted and unweighted tournaments. This problem arises naturally in elections with incompletely specified votes, partially completed sports competitions, and more generally in any scenario where the outcome of ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
We study the problem of computing possible and necessary winners for partially specified weighted and unweighted tournaments. This problem arises naturally in elections with incompletely specified votes, partially completed sports competitions, and more generally in any scenario where the outcome

Possible and Necessary Winner Problem in Social Polls

by Serge Gaspers, Victor Naroditskiy, Toby Walsh, Nina Narodytska
"... Social networks are increasingly being used to conduct polls. We introduce a simple model of such social polling. We suppose agents vote sequentially, but the order in which agents choose to vote is not necessarily fixed. We also suppose that an agent’s vote is influenced by the votes of their frien ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Social networks are increasingly being used to conduct polls. We introduce a simple model of such social polling. We suppose agents vote sequentially, but the order in which agents choose to vote is not necessarily fixed. We also suppose that an agent’s vote is influenced by the votes of their friends who have already voted. Despite its simplicity, this model provides useful insights into a number of areas including social polling, sequential voting, and manipulation. We prove that the number of candidates and the network structure affect the computational complexity of computing which candidate necessarily or possibly can win in such a social poll. For social networks with bounded treewidth and a bounded number of candidates, we provide polynomial algorithms for both problems. In other cases, we prove that computing which candidates necessarily or possibly win are computationally intractable.

Possible and necessary winners in voting trees: Majority graphs vs. profiles

by Maria Silvia Pini, Francesca Rossi, Toby Walsh, Kristen Brent Venable - In Proceedings of the 10th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS , 2011
"... profiles ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Abstract not found

Determining possible and necessary winners under common voting rules given partial orders.

by Lirong Xia , Vincent Conitzer - In Proceedings of the National Conference on Artificial Intelligence (AAAI), , 2008
"... Abstract Usually a voting rule requires agents to give their preferences as linear orders. However, in some cases it is impractical for an agent to give a linear order over all the alternatives. It has been suggested to let agents submit partial orders instead. Then, given a voting rule, a profile ..."
Abstract - Cited by 63 (11 self) - Add to MetaCart
of partial orders, and an alternative (candidate) c, two important questions arise: first, is it still possible for c to win, and second, is c guaranteed to win? These are the possible winner and necessary winner problems, respectively. Each of these two problems is further divided into two sub

unknown title

by unknown authors
"... Computing possible and necessary winners from incomplete partially-ordered preferences 1 ..."
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Computing possible and necessary winners from incomplete partially-ordered preferences 1

unknown title

by unknown authors
"... Computing possible and necessary winners from incomplete partially-ordered preferences 1 ..."
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Computing possible and necessary winners from incomplete partially-ordered preferences 1

Voting procedures with incomplete preferences

by Kathrin Konczak - in Proc. IJCAI-05 Multidisciplinary Workshop on Advances in Preference Handling , 2005
"... We extend the application of a voting procedure (usually defined on complete preference relations over candidates) when the voters ’ preferences consist of partial orders. We define possible (resp. necessary) winners for a given partial preference profile R with respect to a given voting procedure a ..."
Abstract - Cited by 95 (11 self) - Add to MetaCart
We extend the application of a voting procedure (usually defined on complete preference relations over candidates) when the voters ’ preferences consist of partial orders. We define possible (resp. necessary) winners for a given partial preference profile R with respect to a given voting procedure

Incompleteness and Incomparability in Preference Aggregation

by M. S. Pini, F. Rossi, K. B. Venable, T. Walsh - In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007 , 2007
"... We consider how to combine the preferences of multiple agents despite the presence of incompleteness and incomparability in their preference orderings. An agent’s preference ordering may be incomplete because, for example, there is an ongoing preference elicitation process. It may also contain incom ..."
Abstract - Cited by 43 (16 self) - Add to MetaCart
incomparability as this is useful, for example, in multi-criteria scenarios. We focus on the problem of computing the possible and necessary winners, that is, those outcomes which can be or always are the most preferred for the agents. Possible and necessary winners are useful in many scenarios including

ON “GO WITH THE WINNERS”ALGORITHM by

by Sudeepa Roy, To The
"... Aldous and Vazirani proposed the “Go With The Winners ” algorithm [AV94] to boost the success probability in searching for a leaf at the deepest level � of a search tree, by introducing interactions between simulations. They claim high probability of success using only polynomial (in �) number of si ..."
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condition is both necessary and sufficient for a restricted class of search trees. We conjecture that the same condition precisely captures the set of all search trees for which the “Go With The Winners ” algorithm is efficient. Since our condition is weaker than the sufficient condition as provided in [AV

Uncertainty in preference elicitation and aggregation

by Toby Walsh - In AAAI’07 , 2007
"... Uncertainty arises in preference aggregation in several ways. There may, for example, be uncertainty in the votes or the voting rule. Such uncertainty can introduce computational complexity in determining which candidate or candidates can or must win the election. In this paper, we survey recent wor ..."
Abstract - Cited by 51 (13 self) - Add to MetaCart
work in this area and give some new results. We argue, for exam-ple, that the set of possible winners can be computationally harder to compute than the necessary winner. As a second ex-ample, we show that, even if the unknown votes are assumed to be single-peaked, it remains computationally hard to com
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