Research map / Learning theory and algorithms / Submodular and game algorithms
Fair Division with a Secretive Agent
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use only valuations from n − 1 agents to construct rents robust to every room choice by the secretive agent | Rent division with bounded, continuous, strictly decreasing utilities · Rent division | secretive envy-free solution existence | Helped |
| Use quasilinear utilities and maximum-weight matching with a linear program | Secretive rent division · Rent division | computation time | Helped |
| Construct an n-bundle partition using valuations from n − 1 agents | Indivisible-goods allocation with monotone valuations · Indivisible goods | secretive EF1 allocation existence | Helped |
| Iteratively add each good to a universally least-valued bundle while preserving EF1 matchings | Secretive EF1 allocation · Indivisible goods | computation time | Helped |
| Run moving-knife with n − 1 agents rather than requiring valuations from all n agents | Cake division · Cake cutting | proportionality | Helped |
| Use the secretive maximin algorithm under submodular valuations | Indivisible-goods allocation · Indivisible goods | approximate maximin fairness: 1/19-approximate | Helped |
| Use additive rather than submodular valuations | Secretive approximate maximin allocation · Indivisible goods | approximate maximin fairness: 1/2 | Helped |
Closest papers by meaning
- Fair Division via the Cake-Cutting Share (AAAI 2025 · similarity 0.92)
- Almost Envy-Free Allocations of Indivisible Goods or Chores with Entitlements (AAAI 2024 · similarity 0.92)
- On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness (NeurIPS 2025 · similarity 0.92)
- The Complexity of Fair Division of Indivisible Items with Externalities (AAAI 2024 · similarity 0.91)
- Fair Division with Market Values (AAAI 2025 · similarity 0.91)
- Achieving Maximin Share and EFX/EF1 Guarantees Simultaneously (AAAI 2025 · similarity 0.91)
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