NeurIPS 2018poster21 citations
A Mathematical Model For Optimal Decisions In A Representative Democracy
Malik Magdon-Ismail, Lirong Xia
Abstract
Direct democracy, where each voter casts one vote, fails when the average voter competence falls below 50%. This happens in noisy settings when voters have limited information. Representative democracy, where voters choose representatives to vote, can be an elixir in both these situations. We introduce a mathematical model for studying representative democracy, in particular understanding the parameters of a representative democracy that gives maximum decision making capability. Our main result states that under general and natural conditions,
BibTeX
@inproceedings{NEURIPS2018_fa2431bf,
author = {Magdon-Ismail, Malik and Xia, Lirong},
booktitle = {Advances in Neural Information Processing Systems},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {A Mathematical Model For Optimal Decisions In A Representative Democracy},
url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/fa2431bf9d65058fe34e9713e32d60e6-Paper.pdf},
volume = {31},
year = {2018}
}