Manipulation and bribery when aggregating ranked preferences

Ying Zhu, Miroslaw Truszczynski

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationAlgorithmic Decision Theory - 4th International Conference, ADT 2015, Proceedings
EditorsToby Walsh
Number of pages17
StatePublished - 2015
Event4th International Conference on Algorithmic Decision Theory, ADT 2015 - Lexington, United States
Duration: Sep 27 2015Sep 30 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Algorithmic Decision Theory, ADT 2015
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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