The Price of Connectivity in Fair Division

Abstract

We study the allocation of indivisible goods that form an undirected graph and quantify the loss of fairness when we impose a constraint that each agent must receive a connected subgraph. Our focus is on the well-studied fairness notion of maximin share fairness. We introduce the price of connectivity to capture the largest gap between the graph-specific and the unconstrained maximin share, and derive bounds on this quantity which are tight for large classes of graphs in the case of two agents and for paths and stars in the general case. For instance, with two agents we show that for biconnected graphs it is possible to obtain at least 3/4 of the maximin share with connected allocations, while for the remaining graphs the guarantee is at most 1/2. Our work demonstrates several applications of graph-theoretic tools and concepts to fair division problems.

Cite

Text

Bei et al. "The Price of Connectivity in Fair Division." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I6.16651

Markdown

[Bei et al. "The Price of Connectivity in Fair Division." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/bei2021aaai-price/) doi:10.1609/AAAI.V35I6.16651

BibTeX

@inproceedings{bei2021aaai-price,
  title     = {{The Price of Connectivity in Fair Division}},
  author    = {Bei, Xiaohui and Igarashi, Ayumi and Lu, Xinhang and Suksompong, Warut},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {5151-5158},
  doi       = {10.1609/AAAI.V35I6.16651},
  url       = {https://mlanthology.org/aaai/2021/bei2021aaai-price/}
}