Fairness Towards Groups of Agents in the Allocation of Indivisible Items
Abstract
In this paper, we study the problem of matching a set of items to a set of agents partitioned into types so as to balance fairness towards the types against overall utility/efficiency. We extend multiple desirable properties of indivisible goods allocation to our model and investigate the possibility and hardness of achieving combinations of these properties, e.g. we prove that maximizing utilitarian social welfare under constraints of typewise envy-freeness up to one item (TEF1) is computationally intractable. We also define a new concept of waste for this setting, show experimentally that augmenting an existing algorithm with a marginal utility maximization heuristic can produce a TEF1 solution with reduced waste, and also provide a polynomial-time algorithm for computing a non-wasteful TEF1 allocation for binary agent-item utilities.
Cite
Text
Benabbou et al. "Fairness Towards Groups of Agents in the Allocation of Indivisible Items." International Joint Conference on Artificial Intelligence, 2019. doi:10.24963/IJCAI.2019/14Markdown
[Benabbou et al. "Fairness Towards Groups of Agents in the Allocation of Indivisible Items." International Joint Conference on Artificial Intelligence, 2019.](https://mlanthology.org/ijcai/2019/benabbou2019ijcai-fairness/) doi:10.24963/IJCAI.2019/14BibTeX
@inproceedings{benabbou2019ijcai-fairness,
title = {{Fairness Towards Groups of Agents in the Allocation of Indivisible Items}},
author = {Benabbou, Nawal and Chakraborty, Mithun and Elkind, Edith and Zick, Yair},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2019},
pages = {95-101},
doi = {10.24963/IJCAI.2019/14},
url = {https://mlanthology.org/ijcai/2019/benabbou2019ijcai-fairness/}
}