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Lifting preferences over alternatives to preferences over sets of alternatives: The complexity of recognizing desirable families of sets

  • Jan Maly*
  • *Corresponding author for this work

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

Abstract

The problem of lifting a preference order on a set of objects to a preference order on a family of subsets of this set is a fundamental problem with a wide variety of applications in AI. The process is often guided by axioms postulating properties the lifted order should have. Well-known impossibility results by Kannai and Peleg and by Barberà and Pattanaik tell us that some desirable axioms - namely dominance and (strict) independence - are not jointly satisfiable for any linear order on the objects if all non-empty sets of objects are to be ordered. On the other hand, if not all non-empty sets of objects are to be ordered, the axioms are jointly satisfiable for all linear orders on the objects for some families of sets. Such families are very important for applications as they allow for the use of lifted orders, for example, in combinatorial voting. In this paper, we determine the computational complexity of recognizing such families. We show that it is Πp2-complete to decide for a given family of subsets whether dominance and independence or dominance and strict independence are jointly satisfiable for all linear orders on the objects if the lifted order needs to be total. Furthermore, we show that the problem remains coNP-complete if the lifted order can be incomplete. Additionally, we show that the complexity of these problem can increase exponentially if the family of sets is not given explicitly but via a succinct domain restriction.

Original languageEnglish
Title of host publicationProceedings of the 34th AAAI Conference on Artificial Intelligence
Subtitle of host publicationAAAI-20 Technical Tracks 2
Place of PublicationWashington, DC
PublisherAAAI Press
Pages2152-2159
Number of pages8
ISBN (Electronic)9781577358350
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
Duration: 7 Feb 202012 Feb 2020

Publication series

SeriesProceedings of the AAAI Conference on Artificial Intelligence
Number2
Volume34
ISSN2159-5399

Conference

Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/TerritoryUnited States
CityNew York
Period7/02/2012/02/20

Bibliographical note

Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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