Iterative Deliberation via Metric Aggregation

Gil Ben Zvi, Eyal Leizerovich, Nimrod Talmon

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

2 Scopus citations


We investigate an iterative deliberation process for an agent community wishing to make a joint decision. We develop a general model consisting of a community of n agents, each with their initial ideal point in some metric space (X, d), such that in each iteration of the iterative deliberation process, all agents move slightly closer to the current winner, according to some voting rule R. For several natural metric spaces and suitable voting rules for them, we identify conditions under which such an iterative deliberation process is guaranteed to converge.

Original languageEnglish
Title of host publicationAlgorithmic Decision Theory - 7th International Conference, ADT 2021, Proceedings
EditorsDimitris Fotakis, David Ríos Insua
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages15
ISBN (Print)9783030877552
StatePublished - 1 Jan 2021
Event7th International Conference on Algorithmic Decision Theory, ADT 2021 - Toulouse, France
Duration: 3 Nov 20215 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13023 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Conference on Algorithmic Decision Theory, ADT 2021


  • Deliberation
  • Iterative process
  • Metric aggregation
  • Social choice

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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