{"type":"ScholarlyArticle","title":"Better Collective Decisions via Uncertainty Reduction","authors":[{"name":"Shiri Alouf-Heffetz","slug":"shiri-alouf-heffetz","given":"Shiri","family":"Alouf-Heffetz","affiliation":"Ben-Gurion University , Israel; TwoFiveOne Research"},{"name":"Laurent Bulteau","slug":"laurent-bulteau","given":"Laurent","family":"Bulteau","affiliation":"LIGM , CNRS , Université Gustave Eiffel , France"},{"name":"Edith Elkind","slug":"edith-elkind","given":"Edith","family":"Elkind","affiliation":"Department of Computer Science , University of Oxford , UK"},{"name":"Nimrod Talmon","slug":"nimrod-talmon","given":"Nimrod","family":"Talmon","affiliation":"Ben-Gurion University , Israel"},{"name":"Nicholas Teh","slug":"nicholas-teh","given":"Nicholas","family":"Teh","affiliation":"Department of Computer Science , University of Oxford , UK"}],"abstract":"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 make better decisions, i.e., 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, \r\n(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 results and fixed-parameter tractability results.","doi":"10.24963/ijcai.2022/4","url":"https://ijcai.org/proceedings/2022/4","pdf":"https://ijcai.org/proceedings/2022/0004.pdf","markdown":"https://ijcai.org/proceedings/2022/4.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/4","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":4,"pages":{"first":24,"last":30},"keywords":["Agent-based and Multi-agent Systems: Computational Social Choice"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986969","length_sec":89,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985112","length_sec":719,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Bachrach et al., 2010] Yoram Bachrach, Nadja Betzler, and Piotr Faliszewski. 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