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 value of k needed to achieve 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 the fairness requirements.
CITATION STYLE
Halpern, D., & Shah, N. (2021). Fair and Efficient Resource Allocation with Partial Information. In IJCAI International Joint Conference on Artificial Intelligence (pp. 224–230). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2021/32
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