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Related papers: Dynamic Matching and Allocation of Tasks

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We provide a framework to study stability notions for two-sided dynamic matching markets in which matching is one-to-one and irreversible. The framework gives center stage to the set of matchings an agent anticipates would ensue should they…

Theoretical Economics · Economics 2024-10-17 Laura Doval , Pablo Schenone

This work lies in the fusion of experimental economics and data mining. It continues author's previous work on mining behaviour rules of human subjects from experimental data, where game-theoretic predictions partially fail to work.…

Computer Science and Game Theory · Computer Science 2012-11-13 Rustam Tagiew

This paper focuses on the coordination of a large population of dynamic agents with private information over multiple periods. Each agent maximizes the individual utility, while the coordinator determines the market rule to achieve group…

Systems and Control · Computer Science 2015-10-05 Sen Li , Wei Zhang

With artificial intelligence systems becoming ubiquitous in our society, its designers will soon have to start to consider its social dimension, as many of these systems will have to interact among them to work efficiently. With this in…

Artificial Intelligence · Computer Science 2020-06-23 Santiago Cuervo , Marco Alzate

Outsourcing tasks to previously unknown parties is becoming more common. One specific such problem involves matching a set of workers to a set of tasks. Even if the latter have precise requirements, the quality of individual workers is…

Machine Learning · Computer Science 2017-08-01 Philip Ekman , Sebastian Bellevik , Christos Dimitrakakis , Aristide Tossou

Dynamic decisions are pivotal to economic policy making. We show how existing evidence from randomized control trials can be utilized to guide personalized decisions in challenging dynamic environments with budget and capacity constraints.…

Econometrics · Economics 2024-11-26 Karun Adusumilli , Friedrich Geiecke , Claudio Schilter

This paper formally models the strategic repeated interactions between a system, comprising of a machine learning (ML) model and associated explanation method, and an end-user who is seeking a prediction/label and its explanation for a…

Computer Science and Game Theory · Computer Science 2022-08-24 Kavita Kumari , Murtuza Jadliwala , Sumit Kumar Jha , Anindya Maiti

The use of data-driven decision support by public agencies is becoming more widespread and already influences the allocation of public resources. This raises ethical concerns, as it has adversely affected minorities and historically…

Machine Learning · Computer Science 2023-02-03 Sebastian Scher , Simone Kopeinik , Andreas Trügler , Dominik Kowald

We examine two-sided markets where players arrive stochastically over time and are drawn from a continuum of types. The cost of matching a client and provider varies, so a social planner is faced with two contending objectives: a) to reduce…

Computer Science and Game Theory · Computer Science 2020-01-06 Panayotis Mertikopoulos , Heinrich H. Nax , Bary S. R. Pradelski

Stable matching is a fundamental area with many practical applications, such as centralised clearinghouses for school choice or job markets. Recent work has introduced the paradigm of near-feasibility in capacitated matching settings, where…

Computer Science and Game Theory · Computer Science 2026-02-12 Frederik Glitzner

Dynamic game theory is an increasingly popular tool for modeling multi-agent, e.g. human-robot, interactions. Game-theoretic models presume that each agent wishes to minimize a private cost function that depends on others' actions. These…

Robotics · Computer Science 2025-10-17 Cade Armstrong , Ryan Park , Xinjie Liu , Kushagra Gupta , David Fridovich-Keil

In this paper, we study a matching market model on a bipartite network where agents on each side arrive and depart stochastically by a Poisson process. For such a dynamic model, we design a mechanism that decides not only which agents to…

Data Structures and Algorithms · Computer Science 2021-10-22 Naonori Kakimura , Donghao Zhu

The pursuit of long-term fairness involves the interplay between decision-making and the underlying data generating process. In this paper, through causal modeling with a directed acyclic graph (DAG) on the decision-distribution interplay,…

Machine Learning · Computer Science 2023-06-07 Zeyu Tang , Yatong Chen , Yang Liu , Kun Zhang

There are many economic contexts where the productivity and welfare performance of institutions and policies depend on who matches with whom. Examples include caseworkers and job seekers in job search assistance programs, medical doctors…

Econometrics · Economics 2025-07-21 Yagan Hazard , Toru Kitagawa

On two-sided matching platforms such as online dating and recruiting, recommendation algorithms often aim to maximize the total number of matches. However, this objective creates an imbalance, where some users receive far too many matches…

Machine Learning · Computer Science 2026-05-20 Ren Kishimoto , Rikiya Takehi , Koichi Tanaka , Masahiro Nomura , Riku Togashi , Yoji Tomita , Yuta Saito

Dynamic mechanism design is a challenging extension to ordinary mechanism design in which the mechanism designer must make a sequence of decisions over time in the face of possibly untruthful reports of participating agents. Optimizing…

Computer Science and Game Theory · Computer Science 2025-02-18 Michael Curry , Vinzenz Thoma , Darshan Chakrabarti , Stephen McAleer , Christian Kroer , Tuomas Sandholm , Niao He , Sven Seuken

We present an experimental study of decentralized two-sided matching markets with no transfers. Experimental participants are informed of everyone's preferences and can make arbitrary non-binding match offers that get finalized when a…

General Economics · Economics 2024-01-22 Federico Echenique , Alejandro Robinson-Cortés , Leeat Yariv

The challenge in the widely applicable online matching problem lies in making irrevocable assignments while there is uncertainty about future inputs. Most theoretically-grounded policies are myopic or greedy in nature. In real-world…

Machine Learning · Computer Science 2022-11-01 Mohammad Ali Alomrani , Reza Moravej , Elias B. Khalil

The prevalence and importance of algorithmic two-sided marketplaces has drawn attention to the issue of fairness in such settings. Algorithmic decisions are used in assigning students to schools, users to advertisers, and applicants to job…

Machine Learning · Computer Science 2023-06-19 Siddartha Devic , David Kempe , Vatsal Sharan , Aleksandra Korolova

Motivated by equilibrium models of labor markets, we develop a formulation of causal strategic classification in which strategic agents can directly manipulate their outcomes. As an application, we compare employers that anticipate the…

Machine Learning · Statistics 2024-04-23 Seamus Somerstep , Yuekai Sun , Ya'acov Ritov