Fair and Efficient Resource Allocation with Partial Information
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 14 of its 36 references that are in the map. First posted on arXiv 20 May 2021.
Builds on
14 of 36 references.
References · 14
- 2020Best of Both Worlds: Ex-Ante and Ex-Post Fairness in Resource Allocationcited by 15
- 2020EFX Exists for Three Agentscited by 14
- 2020Resolving the Optimal Metric Distortion Conjecturecited by 10
- 2017Fair Allocation of Indivisible Goods: Improvement and Generalizationcited by 9
- 2019An Improved Approximation Algorithm for Maximin Sharescited by 8
- 2019The Price of Fairness for Indivisible Goodscited by 8
- 2016On Truthful Mechanisms for Maximin Share Allocationscited by 6
- 2019Peeking Behind the Ordinal Curtain: Improving Distortion via Cardinal Queriescited by 6
- 2019Communication, Distortion, and Randomness in Metric Votingcited by 6
- 2016Complexity of Manipulating Sequential Allocationcited by 3
- 2017Equilibria in Sequential Allocationcited by 3
- 2018On Fair Division of Indivisible Itemscited by 2
2 more
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.
- 2025Virtual Agent Economiescited by 17
- 2023Best of Both Distortion Worldscited by 3
- 2024Stable Matching with Ties: Approximation Ratios and Learningcited by 2
- 2025Virtual Agent Economies12 Sep 2025
- 2024Stable Matching with Ties: Approximation Ratios and Learning5 Nov 2024
- 2023Best of Both Distortion Worlds30 May 2023