Abstract
Manipulation and bribery have received much attention from the social choice community. We study these concepts for preference formalisms that identify a set of optimal outcomes rather than a single winning outcome. We assume that preferences may be ranked (differ in importance), and we use the Pareto principle adjusted to the case of ranked preferences as the preference aggregation rule. For two important classes of preferences, representing the extreme ends of the spectrum, we provide characterizations of situations when manipulation and bribery is possible, and establish the complexity of the problems to decide that.
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CITATION STYLE
Zhu, Y., & Truszczynski, M. (2015). Manipulation and bribery when aggregating ranked preferences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9346, pp. 86–102). Springer Verlag. https://doi.org/10.1007/978-3-319-23114-3_6
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