Electing the Most Probable Without Eliminating the Irrational: Voting over Intransitive Domains
Abstract
Picking the best alternative in a given set is a well-studied problem at the core of social choice theory. In some applications, one can assume that there is an objectively correct way to compare the alternatives, which, however, cannot be ob-served directly, and individuals ’ preferences over the alternatives (votes) are noisy estimates of this ground truth. The goal of voting in this case is to estimate the ground truth from the votes. In this paradigm, it is usually assumed that the ground truth is a ranking of the alternatives by their true quality. However, sometimes alterna-tives are compared using not one but multiple quality parameters, which may result in cycles in the ground truth as well as in the preferences of the individuals. Motivated by this, we provide a formal model of voting with possibly intransi-tive ground truth and preferences, and investigate the maximum likelihood approach for picking the best alternative in this case. We show that the resulting framework leads to polynomial-time al-gorithms, and also approximates the correspond-ingNP-hard problems in the classic framework. 1
Cite
Text
Elkind and Shah. "Electing the Most Probable Without Eliminating the Irrational: Voting over Intransitive Domains." Conference on Uncertainty in Artificial Intelligence, 2014.Markdown
[Elkind and Shah. "Electing the Most Probable Without Eliminating the Irrational: Voting over Intransitive Domains." Conference on Uncertainty in Artificial Intelligence, 2014.](https://mlanthology.org/uai/2014/elkind2014uai-electing/)BibTeX
@inproceedings{elkind2014uai-electing,
title = {{Electing the Most Probable Without Eliminating the Irrational: Voting over Intransitive Domains}},
author = {Elkind, Edith and Shah, Nisarg},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2014},
pages = {182-191},
url = {https://mlanthology.org/uai/2014/elkind2014uai-electing/}
}