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We study fair division of indivisible goods in a single-parameter environment. In particular, we develop truthful social welfare maximizing mechanisms for fairly allocating indivisible goods. Our fairness guarantees are in terms of solution…

Computer Science and Game Theory · Computer Science 2019-01-29 Siddharth Barman , Ganesh Ghalme , Shweta Jain , Pooja Kulkarni , Shivika Narang

We study the problem of allocating indivisible goods among n agents in a fair manner. For this problem, maximin share (MMS) is a well-studied solution concept which provides a fairness threshold. Specifically, maximin share is defined as…

Computer Science and Game Theory · Computer Science 2017-11-22 Siddharth Barman , Arpita Biswas , Sanath Kumar Krishnamurthy , Y. Narahari

Criteria for a good voting system have been given particularly careful scrutiny in recent years, with general agreement that the core values are fair results, voter power and choice, and local representation. This paper reexamines the basic…

Physics and Society · Physics 2023-03-29 Denis Mollison

We study the problem of fairly dividing indivisible goods among a set of agents under the fairness notion of Any Price Share (APS). APS is known to dominate the widely studied Maximin share (MMS). Since an exact APS allocation may not…

Computer Science and Game Theory · Computer Science 2023-12-15 Pooja Kulkarni , Rucha Kulkarni , Ruta Mehta

In the design and analysis of revenue-maximizing auctions, auction performance is typically measured with respect to a prior distribution over inputs. The most obvious source for such a distribution is past data. The goal is to understand…

Computer Science and Game Theory · Computer Science 2015-11-30 Richard Cole , Tim Roughgarden

We study the problem of aggregating distributions, such as budget proposals, into a collective distribution. An ideal aggregation mechanism would be Pareto efficient, strategyproof, and fair. Most previous work assumes that agents evaluate…

Theoretical Economics · Economics 2025-12-24 Felix Brandt , Matthias Greger , Erel Segal-Halevi , Warut Suksompong

In light of the classic impossibility results of Arrow and Gibbard and Satterthwaite regarding voting with ordinal rules, there has been recent interest in characterizing how well common voting rules approximate the social optimum. In order…

Computer Science and Game Theory · Computer Science 2017-08-29 Yu Cheng , Shaddin Dughmi , David Kempe

Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints.…

Networking and Internet Architecture · Computer Science 2014-01-15 Tobias Harks , Martin Hoefer , Kevin Schewior , Alexander Skopalik

In this paper, we consider the problem of how to fairly dividing $m$ indivisible chores among $n$ agents. The fairness measure we considered here is the maximin share. The previous best known result is that there always exists a…

Computer Science and Game Theory · Computer Science 2021-06-22 Xin Huang , Pinyan Lu

Participatory budgeting (PB) is a democratic process for allocating funds to projects based on the votes of members of the community. Different rules have been used to aggregate participants' votes. Past research has studied the trade-off…

Computer Science and Game Theory · Computer Science 2022-05-26 Roy Fairstein , Reshef Meir , Dan Vilenchik , Kobi Gal

Many high-stakes decisions in health care, public policy, and clinical development require committing to a single policy that will be applied uniformly across a heterogeneous population. Regulatory and fairness standards sometime requires…

Machine Learning · Computer Science 2026-05-12 Tingyu Zhu , Yuhang Wu , Zeyu Zheng

We study a resource allocation setting where $m$ discrete items are to be divided among $n$ agents with additive utilities, and the agents' utilities for individual items are drawn at random from a probability distribution. Since common…

Computer Science and Game Theory · Computer Science 2023-03-20 Pasin Manurangsi , Warut Suksompong

We study envy-free pricing mechanisms in matching markets with $m$ items and $n$ budget constrained buyers. Each buyer is interested in a subset of the items on sale, and she appraises at some single-value every item in her preference-set.…

Computer Science and Game Theory · Computer Science 2016-10-31 Riccardo Colini-Baldeschi , Stefano Leonardi , Qiang Zhang

We study truthful mechanisms for approximating the Maximin-Share (MMS) allocation of agents with additive valuations for indivisible goods. Algorithmically, constant factor approximations exist for the problem for any number of agents. When…

Computer Science and Game Theory · Computer Science 2024-06-12 Ilan Reuven Cohen , Alon Eden , Talya Eden , Arsen Vasilyan

We study the problem of computing maximin share guarantees, a recently introduced fairness notion. Given a set of $n$ agents and a set of goods, the maximin share of a single agent is the best that she can guarantee to herself, if she would…

Computer Science and Game Theory · Computer Science 2018-06-12 Georgios Amanatidis , Evangelos Markakis , Afshin Nikzad , Amin Saberi

A principal selects a team of agents for collaborating on a joint project. The principal aims to design a revenue-optimal contract that incentivize the team of agents to exert costly effort while satisfying fairness constraints. We show…

Computer Science and Game Theory · Computer Science 2025-12-23 Matteo Castiglioni , Junjie Chen , Yingkai Li

We consider an expected-value ranking and selection (R&S) problem where all k solutions' simulation outputs depend on a common parameter whose uncertainty can be modeled by a distribution. We define the most probable best (MPB) to be the…

Methodology · Statistics 2024-04-23 Taeho Kim , Kyoung-kuk Kim , Eunhye Song

When aggregating preferences of agents via voting, two desirable goals are to incentivize agents to participate in the voting process and then identify outcomes that are Pareto efficient. We consider participation as formalized by Brandl,…

Computer Science and Game Theory · Computer Science 2017-05-02 Haris Aziz , Pang Luo , Christine Rizkallah

How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of machine learning systems. Stringent parity constraints on…

Artificial Intelligence · Computer Science 2020-12-09 Angie Peng , Jeff Naecker , Ben Hutchinson , Andrew Smart , Nyalleng Moorosi

Algorithmic decision-making in high-stakes settings can have profound impacts on individuals and populations. While much prior work studies fairness in static settings, recent results show that enforcing static fairness constraints may…

Artificial Intelligence · Computer Science 2026-05-08 Shahin Jabbari , Chen Wang
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