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The celebrated Efficiency-Adjusted Deferred Acceptance mechanism (EADA) improves the efficiency of the DA algorithm via consented priority violations. Notwithstanding its many merits, we show that EADA can improve only two students when an…

Theoretical Economics · Economics 2025-10-13 Taylor Knipe , Josue Ortega

Evidence suggests that participants in strategy-proof matching mechanisms play dominated strategies. To explain the data, we introduce expectation-based loss aversion into a school-choice setting and characterize choice-acclimating personal…

Theoretical Economics · Economics 2024-08-28 Vincent Meisner , Jonas von Wangenheim

This article proposes a characterization of admissions markets that can predict the distribution of students at each school or college under both centralized and decentralized admissions paradigms. The characterization builds on recent…

Theoretical Economics · Economics 2021-07-06 Max Kapur

The deferred acceptance algorithm is an elegant solution to the stable matching problem that guarantees optimality and truthfulness for one side of the market. Despite these desirable guarantees, it is susceptible to strategic misreporting…

Computer Science and Game Theory · Computer Science 2020-12-09 Hadi Hosseini , Fatima Umar , Rohit Vaish

Lotteries are commonly employed in school choice to fairly resolve priority ties; however, current practices typically keep students uninformed about their lottery outcomes at the time of preference submission. This paper advocates for…

Theoretical Economics · Economics 2025-12-04 Lingbo Huang , Jun Zhang

The Deferred Acceptance (DA) algorithm is an elegant procedure for finding a stable matching in two-sided matching markets. It ensures that no pair of agents prefers each other to their matched partners. In this work, we initiate the study…

Computer Science and Game Theory · Computer Science 2025-06-03 Hadi Hosseini , Grzegorz Lisowski , Shraddha Pathak

Stable matching is a fundamental problem studied both in economics and computer science. The task is to find a matching between two sides of agents that have preferences over who they want to be matched with. A matching is stable if no pair…

Computer Science and Game Theory · Computer Science 2024-03-11 Juho Hirvonen , Sara Ranjbaran

The theory of two-sided matching has been extensively developed and applied to many real-life application domains. As the theory has been applied to increasingly diverse types of environments, researchers and practitioners have encountered…

Computer Science and Game Theory · Computer Science 2024-02-05 Sung-Ho Cho , Kei Kimura , Kiki Liu , Kwei-guu Liu , Zhengjie Liu , Zhaohong Sun , Kentaro Yahiro , Makoto Yokoo

The matching literature often recommends market centralization under the assumption that agents know their own preferences and that their preferences are fixed. We find counterevidence to this assumption in a quasi-experiment. In Germany's…

General Economics · Economics 2022-06-07 Julien Grenet , YingHua He , Dorothea Kübler

Prevailing methods of course allocation at undergraduate institutions involve reserving seats to give priority to designated groups of students. We introduce a competitive equilibrium-based mechanism that assigns course seats using student…

Theoretical Economics · Economics 2025-12-24 Daniel Kornbluth , Alexey Kushnir

We conduct an incentivized lab experiment to test participants' ability to understand the DA matching mechanism and the strategyproofness property, conveyed in different ways. We find that while many participants can (using a novel GUI)…

General Economics · Economics 2024-09-30 Yannai A. Gonczarowski , Ori Heffetz , Guy Ishai , Clayton Thomas

Reinforcement-learning agents seek to maximize a reward signal through environmental interactions. As humans, our job in the learning process is to design reward functions to express desired behavior and enable the agent to learn such…

Machine Learning · Computer Science 2024-08-08 Zhiyuan Zhou , Shreyas Sundara Raman , Henry Sowerby , Michael L. Littman

Motivated by applications to online advertising and recommender systems, we consider a game-theoretic model with delayed rewards and asynchronous, payoff-based feedback. In contrast to previous work on delayed multi-armed bandits, we focus…

Computer Science and Game Theory · Computer Science 2020-06-22 Amélie Héliou , Panayotis Mertikopoulos , Zhengyuan Zhou

In real-world settings of the Deferred Acceptance stable matching algorithm, such as the American medical residency match (NRMP), school choice programs, and various national university entrance systems, candidates need to decide which…

Computer Science and Game Theory · Computer Science 2025-06-25 Richard Cole , Pranav Jangir

Students' decisions on whether to take a class are strongly affected by whether their friends plan to take the class with them. A student may prefer to be assigned to a course they likes less, just to be with their friends, rather than…

Artificial Intelligence · Computer Science 2023-09-19 Ilya Khakhiashvili , Lihi Dery , Tal Grinshpoun

The transitivity of preferences is one of the basic assumptions used in the theory of games and decisions. It is often equated with rationality of choice and is considered useful in building rankings. Intransitive preferences are considered…

Quantum Physics · Physics 2015-06-23 Marcin Makowski , Edward W. Piotrowski , Jan Sładkowski

We study a model of binary decisions in a fully connected network of interacting agents. Individual decisions are determined by social influence, coming from direct interactions with neighbours, and a group level pressure that accounts for…

Probability · Mathematics 2021-10-27 Michele Aleandri , Ida Germana Minelli

We study distributed user association in 5G and beyond millimeter-wave enabled heterogeneous networks using matching theory. We propose a novel and efficient distributed matching game, called early acceptance (EA), which allows users to…

Signal Processing · Electrical Eng. & Systems 2020-12-04 Alireza Alizadeh , Mai Vu

This paper investigates a class of games with large strategy spaces, motivated by challenges in AI alignment and language games. We introduce the hidden game problem, where for each player, an unknown subset of strategies consistently…

Artificial Intelligence · Computer Science 2025-10-07 Gon Buzaglo , Noah Golowich , Elad Hazan

Many previous causal inference studies require no interference, that is, the potential outcomes of a unit do not depend on the treatments of other units. However, this no-interference assumption becomes unreasonable when a unit interacts…

Methodology · Statistics 2018-12-24 Xinran Li , Peng Ding , Qian Lin , Dawei Yang , Jun S. Liu