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Epistemic Pairwise Maximin Share

NeurIPS 2026 · Learning theory and algorithms › Submodular and game algorithms · approach: Fair division of indivisible goods · 0 citations (OpenAlex)

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Initiates the study of epistemic pairwise maximin share (EPMMS), proving 4/5-EPMMS existence for additive valuations, exact EPMMS for bivalued (via EGMMS), three additive agents, and two agent types.

Problem

Fair division of indivisible goods: existence of PMMS (and its epistemic relaxation) allocations, which is open for arbitrary additive agents, while EFX and MMS may fail or are hard in general.

Approach

Defines epistemic PMMS, where each agent only needs a hypothetical repartition of others' items (keeping its own bundle) that certifies PMMS. Shows 4/5-EPMMS for additive valuations via envy-cycle elimination on identical rankings with a careful analysis, and extends bivalued MMS algorithms with leximin partitions to obtain EGMMS.

Key results

Surprising findings

Limitations

Experimental setup

Metrics: approximation factor of EPMMS existence of EPMMS/EGMMS allocations

Baselines: EEFX 0.781-PMMS 0.618-PMMS MMS

Builds on: EEFX envy cycle elimination PMMS GMMS PMMS-feasibility

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