A Mathematical Model for Optimal Decisions in a Representative Democracy

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, 1. for fixed voting cost, the optimal number of representatives is linear; 2. for polynomial cost, the optimal number of representatives is logarithmic.

Cite

Text

Magdon-Ismail and Xia. "A Mathematical Model for Optimal Decisions in a Representative Democracy." Neural Information Processing Systems, 2018.

Markdown

[Magdon-Ismail and Xia. "A Mathematical Model for Optimal Decisions in a Representative Democracy." Neural Information Processing Systems, 2018.](https://mlanthology.org/neurips/2018/magdonismail2018neurips-mathematical/)

BibTeX

@inproceedings{magdonismail2018neurips-mathematical,
  title     = {{A Mathematical Model for Optimal Decisions in a Representative Democracy}},
  author    = {Magdon-Ismail, Malik and Xia, Lirong},
  booktitle = {Neural Information Processing Systems},
  year      = {2018},
  pages     = {4702-4711},
  url       = {https://mlanthology.org/neurips/2018/magdonismail2018neurips-mathematical/}
}