IJCAI 2021poster25 citations
Fair and Efficient Resource Allocation with Partial Information
Abstract
We study the fundamental problem of allocating indivisible goods to agents with additive preferences. We consider eliciting from each agent only a ranking of her k most preferred goods instead of her full cardinal valuations. We characterize the amount of preference information that must be elicited in order to satisfy envy-freeness up to one good and approximate maximin share guarantee, two widely studied fairness notions. We also analyze the multiplicative loss in social welfare incurred due to the lack of full information with and without fairness requirements.
Agent-based and Multi-agent Systems: Computational Social ChoiceAgent-based and Multi-agent Systems: Resource AllocationAI Ethics, Trust, Fairness: Fairness
BibTeX
@inproceedings{ijcai2021p32,
title = {Fair and Efficient Resource Allocation with Partial Information},
author = {Halpern, Daniel and Shah, Nisarg},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {224--230},
year = {2021},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2021/32},
url = {https://doi.org/10.24963/ijcai.2021/32},
}