To EFX OR to MMS, That is the Question
Hadi Hosseini, Payas Khurana, Shraddha Pathak, Rohit Vaish
Abstract
We study the agent-wise disjunction of two central fairness notions for indivisible items, where every agent must be either envy-free up to any item (EFX) or maximin-share (MMS) satisfied. One might expect that having a flexible fairness requirement for individual agents will restore existence, especially because the existence of EFX itself resisted resolution for nearly a decade. Surprisingly, it does not. We construct counterexamples with three agents and eight submodular goods, and with three agents and seven submodular chores, significantly strengthening recent EFX impossibility results. On the positive side, we prove existence for additive mixed items with at most three valuation types when one type is a singleton. Additionally, we obtain polynomial-time approximation schemes for additive goods-only and chores-only instances. We also identify a clean separation between the disjunction and its constituents: For additive chores with two valuation types, EFX and MMS are both known to fail, whereas an EFX MMS allocation always exists. Finally, we show that identical additive valuations even admit the conjunction EFX MMS for mixed items. Overall, our results show that allowing flexibility in choosing agent-specific fairness certificates expands the frontier of fair solutions while also uncovering surprising impossibilities.
Create a lesson
Related papers
On the Role of Tie-Breaking Rules in the Convergence of Fictitious Play for Symmetric First-Price Auctions
Benjamin Heymann
Epsilon-Nash Equilibria in History-Dependent SA-MDPs
Brandon Gary Kaplowitz, Dominik Bohnet Zurcher, Akash Agrawal et al.
Core stability recognition for minimum-cost spanning tree games: Parameterized perspective
Michal Dvořák, Ioannis Kakatelis, Dušan Knop
Second-Best Gains from Trade in Matching Markets
Xiaohui Bei, Bo Li, Wenhao Wu et al.
Equilibria of Round-Robin: Computational Hardness and Fairness for Few Subadditive Agents
Paul W. Goldberg, Alexandros Hollender, Giannis Tyrovolas
Estimate then Predict: Convex Formulation for Travel Demand Forecasting
Youngseo Kim, Gioele Zardini, Samitha Samaranayake et al.