Budget-feasible Maximum Nash Social Welfare is Almost Envy-free

Budget-feasible Maximum Nash Social Welfare is Almost Envy-free

Xiaowei Wu, Bo Li, Jiarui Gan

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Main Track. Pages 465-471. https://doi.org/10.24963/ijcai.2021/65

The Nash social welfare (NSW) is a well-known social welfare measurement that balances individual utilities and the overall efficiency. In the context of fair allocation of indivisible goods, it has been shown by Caragiannis et al. (EC 2016 and TEAC 2019) that an allocation maximizing the NSW is envy-free up to one good (EF1). In this paper, we are interested in the fairness of the NSW in a budget-feasible allocation problem, in which each item has a cost that will be incurred to the agent it is allocated to, and each agent has a budget constraint on the total cost of items she receives. We show that a budget-feasible allocation that maximizes the NSW achieves a 1/4-approximation of EF1 and the approximation ratio is tight. The approximation ratio improves gracefully when the items have small costs compared with the agents' budgets; it converges to 1/2 when the budget-cost ratio approaches infinity.
Keywords:
Agent-based and Multi-agent Systems: Computational Social Choice
Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems
AI Ethics, Trust, Fairness: Fairness