Complexity of optimal lobbying in threshold aggregation

Ilan Nehama

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations


Optimal Lobbying is the problem a lobbyist or a campaign manager faces in a full-information voting scenario of a multi-issue referendum when trying to influence the result. The Lobby is faced with a profile that specifies for each voter and each issue whether the voter approves or rejects the issue, and seeks to find the smallest set of voters it must influence to change their vote, for a desired outcome to be obtained. We study the computational complexity of Optimal Lobbying when the issues are aggregated using an anonymous monotone function and the family of desired outcomes is an upward-closed family. We analyze this problem with regard to two parameters: the minimal number of supporters needed to pass an issue, and the size of the maximal minterm of the desired set. We show that for extreme values of the parameters, the problem is tractable, and provide algorithms. On the other hand, we prove intractability of the problem for the complementary cases, which are most of the values of the parameters.

Original languageEnglish
Number of pages2
StatePublished - 2013
Externally publishedYes
Event12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States
Duration: 6 May 201310 May 2013


Conference12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013
Country/TerritoryUnited States
CitySaint Paul, MN


  • Computational complexity
  • Optimal lobbying
  • Parameterized complexity
  • Threshold function


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