Epistemic Pairwise Maximin Share

2026-06-17

AI Summary

This work addresses the long-standing challenges surrounding the existence and computability of the strong fairness notion of pairwise maximin share (PMMS) in indivisible goods allocation. The paper introduces EPMMS, a cognitively relaxed variant of PMMS that weakens the original fairness constraint through a cognitive lens, thereby achieving enhanced tractability under additive valuations. The main contributions include the first formal definition of EPMMS, a proof of its guaranteed existence in canonical settings—such as three agents or two agent types—where MMS allocations may fail to exist, and the design of efficient algorithms: a 4/5-EPMMS approximation for general additive valuations and an exact EPMMS (indeed, the stronger EGMMS) guarantee for binary valuations.

Abstract

We introduce epistemic pairwise maximin share (EPMMS), a new fairness notion for fair division of indivisible goods. Two fundamental notions in this setting are envy-freeness up to any item (EFX) and pairwise maximin share (PMMS), with PMMS being stronger than EFX. While EFX has been extensively studied, far less is known about PMMS. Recent work shows that relaxing EFX via an epistemic perspective leads to substantial progress on the EFX problem, raising the question of whether a similar approach can advance our understanding of PMMS. Motivated by this, we initiate the study of EPMMS, the epistemic relaxation of PMMS. EPMMS is more challenging than EEFX: the key approaches underlying recent progress on epistemic EFX inherently fail to extend to EPMMS. We establish the following results. (1) For additive valuations, $4/5$-EPMMS allocations exist and can be efficiently computed. (2) For bivalued valuations, EPMMS allocations exist and can be efficiently computed; in fact, we obtain the stronger guarantee of epistemic groupwise maximin share (EGMMS), which also strengthens the existence of MMS allocations for this setting. (3) We prove that EPMMS allocations exist in two settings where MMS allocations need not exist: instances with three additive agents or two types of additive agents.

Problem

• fair division
• indivisible goods
• pairwise maximin share
• epistemic fairness
• PMMS

Innovation

• Epistemic fairness
• Maximin share
• Fair division
• Indivisible goods
• Computational fairness