Equitable Allocations of Indivisible Goods

Equitable Allocations of Indivisible Goods

Rupert Freeman, Sujoy Sikdar, Rohit Vaish, Lirong Xia

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Main track. Pages 280-286. https://doi.org/10.24963/ijcai.2019/40

In fair division, equitability dictates that each participant receives the same level of utility. In this work, we study equitable allocations of indivisible goods among agents with additive valuations. While prior work has studied (approximate) equitability in isolation, we consider equitability in conjunction with other well-studied notions of fairness and economic efficiency. We show that the Leximin algorithm produces an allocation that satisfies equitability up to any good and Pareto optimality. We also give a novel algorithm that guarantees Pareto optimality and equitability up to one good in pseudopolynomial time.  Our experiments on real-world preference data reveal that approximate envy-freeness, approximate equitability, and Pareto optimality can often be achieved simultaneously.
Keywords:
Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems
Agent-based and Multi-agent Systems: Computational Social Choice
Agent-based and Multi-agent Systems: Resource Allocation