Better Collective Decisions via Uncertainty Reduction

Shiri Alouf-Heffetz, Laurent Bulteau, Edith Elkind, Nimrod Talmon, Nicholas Teh

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


We consider an agent community wishing to decide on several binary issues by means of issue-by-issue majority voting. For each issue and each agent, one of the two options is better than the other. However, some of the agents may be confused about some of the issues, in which case they may vote for the option that is objectively worse for them. A benevolent external party wants to help the agents to select the majority-preferred option for as many issues as possible. This party may have one of the following tools at its disposal: (1) educating some of the agents, so as to enable them to vote correctly on all issues, (2) appointing a subset of highly competent agents to make decisions on behalf of the entire group, or (3) guiding the agents on how to delegate their votes to other agents, in a way that is consistent with the agents' opinions. For each of these tools, we study the complexity of the decision problem faced by this external party, obtaining both NP-hardness and fixed-parameter tractability results.

Original languageAmerican English
Title of host publicationProceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
EditorsLuc De Raedt
Number of pages7
ISBN (Electronic)9781956792003
StatePublished - 1 Jan 2022
Event31st International Joint Conference on Artificial Intelligence, IJCAI 2022 - Vienna, Austria
Duration: 23 Jul 202229 Jul 2022

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence


Conference31st International Joint Conference on Artificial Intelligence, IJCAI 2022

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence


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