Fair and Efficient Completion of Indivisible Goods

We formulate the problem of fair and efficient completion of indivisible goods, defined as follows: Given a partial allocation of indivisible goods among agents, does there exist an allocation of the remaining goods (i.e., a completion) that satisfies fairness and economic efficiency guarantees of interest? We study the computational complexity of the completion problem for prominent fairness and efficiency notions such as envy-freeness up to one good (EF1), proportionality up to one good (Prop1), maximin share (MMS), and Pareto optimality (PO), and focus on the class of additive valuations as well as its subclasses such as binary additive and lexicographic valuations. We find that while the completion problem is significantly harder than the standard fair division problem (wherein the initial partial allocation is empty), the consideration of restricted preferences facilitates positive algorithmic results for threshold-based fairness notions (Prop1 and MMS). On the other hand, the completion problem remains computationally intractable for envy-based notions such as EF1 and EF1+PO even under restricted preferences.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i13.33537
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

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article

Fair and Efficient Completion of Indivisible Goods

Ayumi Igarashi, Rohit Vaish, Vishwa Prakash HV
Proceedings of the AAAI Conference on Artificial Intelligence
Blockchain Technology Applications and Security
article

Fair and Efficient Completion of Indivisible Goods

Ayumi Igarashi, Rohit Vaish, Vishwa Prakash HV
article en

Abstract

We formulate the problem of fair and efficient completion of indivisible goods, defined as follows: Given a partial allocation of indivisible goods among agents, does there exist an allocation of the remaining goods (i.e., a completion) that satisfies fairness and economic efficiency guarantees of interest? We study the computational complexity of the completion problem for prominent fairness and efficiency notions such as envy-freeness up to one good (EF1), proportionality up to one good (Prop1), maximin share (MMS), and Pareto optimality (PO), and focus on the class of additive valuations as well as its subclasses such as binary additive and lexicographic valuations. We find that while the completion problem is significantly harder than the standard fair division problem (wherein the initial partial allocation is empty), the consideration of restricted preferences facilitates positive algorithmic results for threshold-based fairness notions (Prop1 and MMS). On the other hand, the completion problem remains computationally intractable for envy-based notions such as EF1 and EF1+PO even under restricted preferences.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(13)
Chennai Mathematical Institute (IN), Indian Institute of Technology Delhi (IN), The University of Tokyo (JP)
Department of Science and Technology, Ministry of Science and Technology, India, Science and Engineering Research Board
Openalex Percentile: Top 74%
Blockchain Technology Applications and Security
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Fair and Efficient Completion of Indivisible Goods — Ayumi Igarashi, Rohit Vaish, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS