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相关论文: A tight negative example for MMS fair allocations

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We initiate the work on maximin share (MMS) fair allocation of m indivisible chores to n agents using only their ordinal preferences, from both algorithmic and mechanism design perspectives. The previous best-known approximation is 2-1/n by…

计算机科学与博弈论 · 计算机科学 2020-12-29 Haris Aziz , Bo Li , Xiaowei Wu

We study the problem of fairly allocating a set of m indivisible chores (items with non-positive value) to n agents. We consider the desirable fairness notion of 1-out-of-d maximin share (MMS) -- the minimum value that an agent can…

计算机科学与博弈论 · 计算机科学 2022-01-20 Hadi Hosseini , Andrew Searns , Erel Segal-Halevi

We consider the problem of fair allocation of indivisible goods to $n$ agents, with no transfers. When agents have equal entitlements, the well established notion of the maximin share (MMS) serves as an attractive fairness criterion, where…

计算机科学与博弈论 · 计算机科学 2021-11-16 Moshe Babaioff , Tomer Ezra , Uriel Feige

We study the multi-party randomized communication complexity of computing a fair allocation of $m$ indivisible goods to $n < m$ equally entitled agents. We first consider MMS allocations, allocations that give every agent at least her…

计算机科学与博弈论 · 计算机科学 2024-07-11 Uriel Feige

We consider the problem of fair allocation of indivisible items to agents that have arbitrary entitlements to the items. Every agent $i$ has a valuation function $v_i$ and an entitlement $b_i$, where entitlements sum up to~1. Which…

计算机科学与博弈论 · 计算机科学 2024-05-24 Moshe Babaioff , Uriel Feige

We consider the problem of guaranteeing maximin-share (MMS) when allocating a set of indivisible items to a set of agents with fractionally subadditive (XOS) valuations. For XOS valuations, it has been previously shown that for some…

计算机科学与博弈论 · 计算机科学 2023-10-24 Hannaneh Akrami , Kurt Mehlhorn , Masoud Seddighin , Golnoosh Shahkarami

We study the problem of allocating $m$ indivisible goods among $n$ agents, where each agent's valuation is fractionally subadditive (XOS). With respect to AnyPrice Share (APS) fairness, Kulkarni et al. (2024) showed that, when agents have…

计算机科学与博弈论 · 计算机科学 2026-01-15 Ziheng Chen , Bo Li , Zihan Luo , Jialin Zhang

We study the fair division of indivisible items. In the general model, the goal is to allocate $m$ indivisible items to $n$ agents while satisfying fairness criteria such as MMS, EF1, and EFX. We also study a recently-introduced graphical…

计算机科学与博弈论 · 计算机科学 2025-10-15 Kevin Hsu

We study the problem of fair allocation of a set of indivisible goods among $n$ agents with $k$ distinct additive valuations, with the goal of achieving approximate envy-freeness up to any good ($\alpha-\mathrm{EFX}$). It is known that EFX…

计算机科学与博弈论 · 计算机科学 2025-08-22 Vishwa Prakash HV , Ruta Mehta , Prajakta Nimbhorkar

We investigate fairness in the allocation of indivisible items among groups of agents using the notion of maximin share (MMS). While previous work has shown that no nontrivial multiplicative MMS approximation can be guaranteed in this…

计算机科学与博弈论 · 计算机科学 2025-03-06 Pasin Manurangsi , Warut Suksompong

We study envy-free allocations of indivisible goods to agents in settings where each agent is unaware of the goods allocated to other agents. In particular, we propose the maximin aware (MMA) fairness measure, which guarantees that every…

计算机科学与博弈论 · 计算机科学 2019-10-29 Hau Chan , Jing Chen , Bo Li , Xiaowei Wu

We consider the problem of allocating $m$ indivisible chores to $n$ agents with additive disvaluation (cost) functions. It is easy to show that there are picking sequences that give every agent (that uses the greedy picking strategy) a…

计算机科学与博弈论 · 计算机科学 2022-11-28 Uriel Feige , Xin Huang

The real-world deployment of fair allocation algorithms usually involves a heterogeneous population of users, which makes it challenging for the users to get complete knowledge of the allocation except for their own bundles. Chan et al.…

计算机科学与博弈论 · 计算机科学 2023-08-31 Tianze Wei , Bo Li , Minming Li

We study the problem of fair allocation of a set of indivisible items among agents with additive valuations, under cardinality constraints. In this setting, the items are partitioned into categories, each with its own limit on the number of…

计算机科学与博弈论 · 计算机科学 2022-08-11 Halvard Hummel , Magnus Lie Hetland

We consider item allocation to individual agents who have additive valuations, in settings in which there are protected groups, and the allocation needs to give each protected group its "fair" share of the total welfare. Informally, within…

计算机科学与博弈论 · 计算机科学 2022-04-15 Uriel Feige , Yehonatan Tahan

We study several fairness notions in allocating indivisible chores (i.e., items with non-positive values) to agents who have additive and submodular cost functions. The fairness criteria we are concern with are envy-free up to any item…

计算机科学与博弈论 · 计算机科学 2021-09-29 Ankang Sun , Bo Chen , Xuan Vinh Doan

We consider the problem of fairly and efficiently allocating indivisible items (goods or bads) under capacity constraints. In this setting, we are given a set of categorized items. Each category has a capacity constraint (the same for all…

计算机科学与博弈论 · 计算机科学 2023-03-01 Hila Shoshan , Erel Segal-Halevi , Noam Hazon

We consider fair allocation of a set $M$ of indivisible goods to $n$ equally-entitled agents, with no monetary transfers. Every agent $i$ has a valuation $v_i$ from some given class of valuation functions. A share $s$ is a function that…

理论经济学 · 经济学 2022-05-17 Moshe Babaioff , Uriel Feige

When dividing items among agents, two of the most widely studied fairness notions are envy-freeness and proportionality. We consider a setting where $m$ chores are allocated to $n$ agents and the disutility of each chore for each agent is…

计算机科学与博弈论 · 计算机科学 2025-04-30 Pasin Manurangsi , Warut Suksompong

We study the problem of fairly and efficiently allocating a set of items among strategic agents with additive valuations, where items are either all indivisible or all divisible. When items are goods, numerous positive and negative results…

计算机科学与博弈论 · 计算机科学 2025-07-08 Bo Li , Biaoshuai Tao , Fangxiao Wang , Xiaowei Wu , Mingwei Yang , Shengwei Zhou