First-Choice Maximality Meets Ex-ante and Ex-post Fairness
Xiaoxi Guo, Sujoy Sikdar, Lirong Xia, Yongzhi Cao, Hanpin Wang
Abstract
For the assignment problem where multiple indivisible items are allocated to a group of agents given their ordinal preferences, we design randomized mechanisms that satisfy first-choice maximality (FCM), i.e., maximizing the number of agents assigned their first choices, together with Pareto efficiency (PE). Our mechanisms also provide guarantees of ex-ante and ex-post fairness. The generalized eager Boston mechanism is ex-ante envy-free, and ex-post envy-free up to one item (EF1). The generalized probabilistic Boston mechanism is also ex-post EF1, and satisfies ex-ante efficiency instead of fairness. We also show that no strategyproof mechanism satisfies ex-post PE, EF1, and FCM simultaneously. In doing so, we expand the frontiers of simultaneously providing efficiency and both ex-ante and ex-post fairness guarantees for the assignment problem.
BibTeX
@inproceedings{ijcai2023p303,
title = {First-Choice Maximality Meets Ex-ante and Ex-post Fairness},
author = {Guo, Xiaoxi and Sikdar, Sujoy and Xia, Lirong and Cao, Yongzhi and Wang, Hanpin},
booktitle = {Proceedings of the Thirty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-23}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Edith Elkind},
pages = {2719--2727},
year = {2023},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2023/303},
url = {https://doi.org/10.24963/ijcai.2023/303},
}