Committee selection with intraclass and interclass synergies

Rani Izsak, Nimrod Talmon, Gerhard J. Woeginger

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

Abstract

Voting is almost never done in void, as usually there are some relations between the alternatives on which the voters vote on. These relations shall be taken into consideration when selecting a winning committee of some given multiwinner election. As taking into account all possible relations between the alternatives is generally computationally intractable, in this paper we consider classes of alternatives; intuitively, the number of classes is significantly smaller than the number of alternatives, and thus there is some hope in reaching computational tractability. We model both intraclass relations and interclass relations by functions, which we refer to as synergy functions, and study the computational complexity of identifying the best committee, taking into account those synergy functions. Our model accommodates both positive and negative relations between alternatives; further, our efficient algorithms can also deal with a rich class of diversity wishes, which we show how to model using synergy functions.

Original languageAmerican English
Title of host publication32nd AAAI Conference on Artificial Intelligence, AAAI 2018
Pages1071-1078
Number of pages8
ISBN (Electronic)9781577358008
StatePublished - 1 Jan 2018
Externally publishedYes
Event32nd AAAI Conference on Artificial Intelligence, AAAI 2018 - New Orleans, United States
Duration: 2 Feb 20187 Feb 2018

Publication series

Name32nd AAAI Conference on Artificial Intelligence, AAAI 2018

Conference

Conference32nd AAAI Conference on Artificial Intelligence, AAAI 2018
Country/TerritoryUnited States
CityNew Orleans
Period2/02/187/02/18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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