A Better Algorithm for Societal Tradeoffs
Abstract
In the societal tradeoffs problem, each agent perceives certain quantitative tradeoffs between pairs of activities, and the goal is to aggregate these tradeoffs across agents. This is a problem in social choice; specifically, it is a type of quantitative judgment aggregation problem. A natural rule for this problem was axiomatized by Conitzer et al. [AAAI 2016]; they also provided several algorithms for computing the outcomes of this rule. In this paper, we present a significantly improved algorithm and evaluate it experimentally. Our algorithm is based on a tight connection to minimum-cost flow that we exhibit. We also show that our algorithm cannot be improved without breakthroughs on min-cost flow.
Cite
Text
Zhang et al. "A Better Algorithm for Societal Tradeoffs." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33012229Markdown
[Zhang et al. "A Better Algorithm for Societal Tradeoffs." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/zhang2019aaai-better/) doi:10.1609/AAAI.V33I01.33012229BibTeX
@inproceedings{zhang2019aaai-better,
title = {{A Better Algorithm for Societal Tradeoffs}},
author = {Zhang, Hanrui and Cheng, Yu and Conitzer, Vincent},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {2229-2236},
doi = {10.1609/AAAI.V33I01.33012229},
url = {https://mlanthology.org/aaai/2019/zhang2019aaai-better/}
}