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Related papers: Fair Interventions in Weighted Congestion Games

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This paper addresses the matter of inequality in network formation games. We employ a quantity that we are calling the Nash Inequality Ratio (NIR), defined as the maximal ratio between the highest and lowest costs incurred to individual…

Computer Science and Game Theory · Computer Science 2014-10-21 Samuel D. Johnson , Raissa M. D'Souza

We show that many machine learning goals, such as improved fairness metrics, can be expressed as constraints on the model's predictions, which we call rate constraints. We study the problem of training non-convex models subject to these…

Machine Learning · Computer Science 2018-09-13 Andrew Cotter , Heinrich Jiang , Serena Wang , Taman Narayan , Maya Gupta , Seungil You , Karthik Sridharan

Computing Nash equilibrium policies is a central problem in multi-agent reinforcement learning that has received extensive attention both in theory and in practice. However, provable guarantees have been thus far either limited to fully…

Analysis of efficiency of outcomes in game theoretic settings has been a main item of study at the intersection of economics and computer science. The notion of the price of anarchy takes a worst-case stance to efficiency analysis,…

Computer Science and Game Theory · Computer Science 2017-07-05 Darrell Hoy , Denis Nekipelov , Vasilis Syrgkanis

We study fair allocation of indivisible public goods subject to cardinality (budget) constraints. In this model, we have n agents and m available public goods, and we want to select $k \leq m$ goods in a fair and efficient manner. We first…

Computer Science and Game Theory · Computer Science 2021-07-22 Jugal Garg , Pooja Kulkarni , Aniket Murhekar

We study the problem of fairly allocating a set of indivisible goods among agents with additive valuations. The extent of fairness of an allocation is measured by its Nash social welfare, which is the geometric mean of the valuations of the…

Computer Science and Game Theory · Computer Science 2018-07-23 Siddharth Barman , Sanath Kumar Krishnamurthy , Rohit Vaish

We study a multi-leader single-follower congestion game where multiple users (leaders) choose one resource out of a set of resources and, after observing the realized loads, an adversary (single-follower) attacks the resources with maximum…

Computer Science and Game Theory · Computer Science 2021-12-15 Tobias Harks , Mona Henle , Max Klimm , Jannik Matuschke , Anja Schedel

The complexity of computing equilibrium refinements has been at the forefront of algorithmic game theory research, but it has remained open in the seminal class of potential games; we close this fundamental gap in this paper. We first show…

Computer Science and Game Theory · Computer Science 2026-02-11 Ioannis Anagnostides , Maria-Florina Balcan , Kiriaki Fragkia , Tuomas Sandholm , Emanuel Tewolde , Brian Hu Zhang

Congestion games constitute an important class of games in which computing an exact or even approximate pure Nash equilibrium is in general {\sf PLS}-complete. We present a surprisingly simple polynomial-time algorithm that computes…

Computer Science and Game Theory · Computer Science 2011-07-14 Ioannis Caragiannis , Angelo Fanelli , Nick Gravin , Alexander Skopalik

We consider the problem of allocating $m$ indivisible chores among $n$ agents with possibly different weights, aiming for a solution that is both fair and efficient. Specifically, we focus on the classic fairness notion of proportionality…

Computer Science and Game Theory · Computer Science 2025-10-14 Jugal Garg , Eklavya Sharma , Xiaowei Wu

We initiate the study of fairness in reinforcement learning, where the actions of a learning algorithm may affect its environment and future rewards. Our fairness constraint requires that an algorithm never prefers one action over another…

Machine Learning · Computer Science 2017-08-08 Shahin Jabbari , Matthew Joseph , Michael Kearns , Jamie Morgenstern , Aaron Roth

We study the problem of allocating a set of indivisible goods among a set of agents in a fair and efficient manner. An allocation is said to be fair if it is envy-free up to one good (EF1), which means that each agent prefers its own bundle…

Computer Science and Game Theory · Computer Science 2018-05-14 Siddharth Barman , Sanath Kumar Krishnamurthy , Rohit Vaish

We study a novel problem of fairness in ranking aimed at minimizing the amount of individual unfairness introduced when enforcing group-fairness constraints. Our proposal is rooted in the distributional maxmin fairness theory, which uses…

Machine Learning · Computer Science 2021-06-18 David Garcia-Soriano , Francesco Bonchi

We study the basic allocation problem of assigning resources to players so as to maximize fairness. This is one of the few natural problems that enjoys the intriguing status of having a better estimation algorithm than approximation…

Data Structures and Algorithms · Computer Science 2016-11-24 Chidambaram Annamalai , Christos Kalaitzis , Ola Svensson

We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the…

Computer Science and Game Theory · Computer Science 2012-06-05 Yu Wu , Loc Bui , Ramesh Johari

The assignment game is a classical model for profit sharing and a cornerstone of cooperative game theory. While an imputation in its core guarantees fairness among coalitions, it provides no fairness guarantee at the level of individual…

Computer Science and Game Theory · Computer Science 2025-11-21 Vijay V. Vazirani

We study bottleneck routing games where the social cost is determined by the worst congestion on any edge in the network. Bottleneck games have been studied in the literature by having the player's utility costs to be determined by the…

Computer Science and Game Theory · Computer Science 2009-11-24 Rajgopal Kannan , Costas Busch

We study the max-min fair allocation problem in which a set of $m$ indivisible items are to be distributed among $n$ agents such that the minimum utility among all agents is maximized. In the restricted setting, the utility of each item $j$…

Discrete Mathematics · Computer Science 2016-11-28 T-H. Hubert Chan , Zhihao Gavin Tang , Xiaowei Wu

How do rational agents self-organize when trying to connect to a common target? We study this question with a simple tree formation game which is related to the well-known fair single-source connection game by Anshelevich et al. (FOCS'04)…

Computer Science and Game Theory · Computer Science 2020-09-24 Davide Bilò , Tobias Friedrich , Pascal Lenzner , Anna Melnichenko , Louise Molitor

Two important metrics for measuring the quality of routing paths are the maximum edge congestion $C$ and maximum path length $D$. Here, we study bicriteria in routing games where each player $i$ selfishly selects a path that simultaneously…

Computer Science and Game Theory · Computer Science 2008-02-01 Costas Busch , Rajgopal Kannan
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