Weighted Fair Division with Matroid-Rank Valuations: Monotonicity and Strategyproofness
arXiv:2303.14454 · doi:10.1016/j.mathsocsci.2023.09.004
Abstract
We study the problem of fairly allocating indivisible goods to agents with weights corresponding to their entitlements. Previous work has shown that, when agents have binary additive valuations, the maximum weighted Nash welfare rule is resource-, population-, and weight-monotone, satisfies group-strategyproofness, and can be implemented in polynomial time. We generalize these results to the class of weighted additive welfarist rules with concave functions and agents with matroid-rank (also known as binary submodular) valuations.
Appears in the 16th International Symposium on Algorithmic Game Theory (SAGT), 2023
References in corpus (5)
- On Maximum Weighted Nash Welfare for Binary Valuations
- Existence and Computation of Maximin Fair Allocations Under Matroid-Rank Valuations
- A Characterization of Maximum Nash Welfare for Indivisible Goods
- Extending the Characterization of Maximum Nash Welfare
- For One and All: Individual and Group Fairness in the Allocation of Indivisible Goods