TY - GEN
T1 - Which is the fairest (Rent Division) of them all?
AU - Gal, Ya'akov
AU - Mash, Moshe
AU - Procaccia, Ariel D.
AU - Zick, Yair
N1 - Funding Information:
This work was supported by EU FP7 FET project, grant agreement n.600854; by the National Science Foundation under grants IIS-1350598, CCF-1215883, and CCF-1525932; and by a Sloan Research Fellowship.
PY - 2016/7/21
Y1 - 2016/7/21
N2 - What is a fair way to assign rooms to several housemates, and divide the rent between them? This is not just a theoretical question: many people have used the Spliddit website to obtain envy-free solutions to rent division instances. But envy freeness, in and of itself, is insufficient to guarantee outcomes that people view as intuitive and acceptable. We therefore focus on solutions that optimize a criterion of social justice, subject to the envy freeness constraint, in order to pinpoint the "fairest" solutions. We develop a general algorithmic framework that enables the computation of such solutions in polynomial time. We then study the relations between natural optimization objectives, and identify the maximin solution, which maximizes the minimum utility subject to envy freeness, as the most attractive. We demonstrate, in theory and using experiments on real data from Spliddit, that the maximin solution gives rise to significant gains in terms of our optimization objectives. Finally, a user study with Spliddit users as subjects demonstrates that people find the maximin solution to be significantly fairer than arbitrary envy-free solutions; this user study is unprecedented in that it asks people about their real-world rent division instances. Based on these results, the maximin solution has been deployed on Spliddit since April 2015.
AB - What is a fair way to assign rooms to several housemates, and divide the rent between them? This is not just a theoretical question: many people have used the Spliddit website to obtain envy-free solutions to rent division instances. But envy freeness, in and of itself, is insufficient to guarantee outcomes that people view as intuitive and acceptable. We therefore focus on solutions that optimize a criterion of social justice, subject to the envy freeness constraint, in order to pinpoint the "fairest" solutions. We develop a general algorithmic framework that enables the computation of such solutions in polynomial time. We then study the relations between natural optimization objectives, and identify the maximin solution, which maximizes the minimum utility subject to envy freeness, as the most attractive. We demonstrate, in theory and using experiments on real data from Spliddit, that the maximin solution gives rise to significant gains in terms of our optimization objectives. Finally, a user study with Spliddit users as subjects demonstrates that people find the maximin solution to be significantly fairer than arbitrary envy-free solutions; this user study is unprecedented in that it asks people about their real-world rent division instances. Based on these results, the maximin solution has been deployed on Spliddit since April 2015.
KW - Computational fair division
UR - http://www.scopus.com/inward/record.url?scp=84983488971&partnerID=8YFLogxK
U2 - 10.1145/2940716.2940724
DO - 10.1145/2940716.2940724
M3 - Conference contribution
AN - SCOPUS:84983488971
T3 - EC 2016 - Proceedings of the 2016 ACM Conference on Economics and Computation
SP - 67
EP - 84
BT - EC 2016 - Proceedings of the 2016 ACM Conference on Economics and Computation
PB - Association for Computing Machinery, Inc
T2 - 17th ACM Conference on Economics and Computation, EC 2016
Y2 - 24 July 2016 through 28 July 2016
ER -