Abstract / Description of output
When an agent votes, she typically ranks the set of available alternatives. Occasionally, she may also wish to report the intensity of her preferences by indicating adjacent pairs of alternatives in her ranking between which her preference is acutely decisive; for instance, she may suggest that she likes alternative a more than b, but b much more than c. We design near-optimal voting rules which aggregate such preference rankings with intensities using the recently-popular distortion framework. We also show that traditional voting rules, which aggregate preference rankings while ignoring (or not eliciting) intensities, can incur significant welfare loss.
Original language | English |
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Title of host publication | Proceedings of the 37th AAAI Conference on Artificial Intelligence |
Editors | Brian Williams, Yiling Chen, Jennifer Neville |
Publisher | AAAI Press |
Pages | 5697-5704 |
Number of pages | 8 |
Volume | 37 |
Edition | 5 |
ISBN (Electronic) | 9781577358800 |
DOIs | |
Publication status | Published - 26 Jun 2023 |
Event | The 37th AAAI Conference on Artificial Intelligence - Walter E. Washington Convention Center, Washington, United States Duration: 7 Feb 2023 → 14 Feb 2023 https://aaai.org/Conferences/AAAI-23/ |
Publication series
Name | Proceedings of the AAAI Conference on Artificial Intelligence |
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Publisher | AAAI Press |
ISSN (Print) | 2159-5399 |
ISSN (Electronic) | 2374-3468 |
Conference
Conference | The 37th AAAI Conference on Artificial Intelligence |
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Abbreviated title | AAAI-23 |
Country/Territory | United States |
City | Washington |
Period | 7/02/23 → 14/02/23 |
Internet address |
Keywords / Materials (for Non-textual outputs)
- GTEP
- social choice
- social voting