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We study mechanism design for public-good provision under a noisy privacy-preserving transformation of individual agents' reported preferences. The setting is a standard binary model with transfers and quasi-linear utility. Agents report…

Theoretical Economics · Economics 2024-05-21 Farzad Pourbabaee , Federico Echenique

Crowdsourcing is now widely used to replace judgement by an expert authority with an aggregate evaluation from a number of non-experts, in applications ranging from rating and categorizing online content to evaluation of student assignments…

Computer Science and Game Theory · Computer Science 2013-03-05 Anirban Dasgupta , Arpita Ghosh

We consider a fundamental dynamic allocation problem motivated by the problem of $\textit{securities lending}$ in financial markets, the mechanism underlying the short selling of stocks. A lender would like to distribute a finite number of…

Computer Science and Game Theory · Computer Science 2019-12-16 Emily Diana , Michael Kearns , Seth Neel , Aaron Roth

We construct a model of an exchange economy in which agents trade assets contingent on an observable signal, the probability of which depends on public opinion. The agents in our model are replaced occasionally and each person updates…

Theoretical Economics · Economics 2022-04-28 Jean-Philippe Bouchaud , Roger Farmer

We study the consequences of information asymmetries and misaligned incentives in settings with multiple independent agents. We model an interaction between a Sender, who holds vital private information but cannot act, and a Receiver, who…

Multiagent Systems · Computer Science 2026-05-13 Nanda Kishore Sreenivas , Kate Larson

We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a…

Computer Science and Game Theory · Computer Science 2014-01-16 Radu Jurca , Boi Faltings

The ``impossibility theorem'' -- which is considered foundational in algorithmic fairness literature -- asserts that there must be trade-offs between common notions of fairness and performance when fitting statistical models, except in two…

Machine Learning · Computer Science 2023-02-14 Andrew Bell , Lucius Bynum , Nazarii Drushchak , Tetiana Herasymova , Lucas Rosenblatt , Julia Stoyanovich

In this work, we study the system of interacting non-cooperative two Q-learning agents, where one agent has the privilege of observing the other's actions. We show that this information asymmetry can lead to a stable outcome of population…

Machine Learning · Computer Science 2021-01-26 Ezra Tampubolon , Haris Ceribasic , Holger Boche

A principal who values an object allocates it to one or more agents. Agents learn private information (signals) from an information designer about the allocation payoff to the principal. Monetary transfer is not available but the principal…

Theoretical Economics · Economics 2022-10-31 Yi-Chun Chen , Gaoji Hu , Xiangqian Yang

This paper introduces a novel criterion, persuasiveness, to select equilibria in signaling games. In response to the Stiglitz critique, persuasiveness focuses on the comparison across equilibria. An equilibrium is more persuasive than an…

Theoretical Economics · Economics 2025-11-04 Haoyuan Zeng

When making a decision as a group, there are two primary paradigms: aggregating preferences (e.g. voting, mechanism design) and aggregating information (e.g. discussion, consulting, forecasting). Almost all formally-studied group…

Computer Science and Game Theory · Computer Science 2025-03-03 Mary Monroe , Bo Waggoner

We study online Bayesian persuasion problems in which an informed sender repeatedly faces a receiver with the goal of influencing their behavior through the provision of payoff-relevant information. Previous works assume that the sender has…

Computer Science and Game Theory · Computer Science 2024-11-12 Francesco Bacchiocchi , Matteo Bollini , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

The literature on strategic communication originated with the influential cheap talk model, which precedes the Bayesian persuasion model by three decades. This model describes an interaction between two agents: sender and receiver. The…

Computer Science and Game Theory · Computer Science 2024-09-11 Yakov Babichenko , Inbal Talgam-Cohen , Haifeng Xu , Konstantin Zabarnyi

We consider the problem of allocating heterogeneous and indivisible goods among strategic agents, with preferences over subsets of goods, when there is no medium of exchange. This model captures the well studied problem of fair allocation…

Computer Science and Game Theory · Computer Science 2026-04-27 Moshe Babaioff , Noam Manaker Morag

Studying games in the complete information model makes them analytically tractable. However, large $n$ player interactions are more realistically modeled as games of incomplete information, where players may know little to nothing about the…

Computer Science and Game Theory · Computer Science 2015-12-11 Ryan Rogers , Aaron Roth

We study a crowdsourcing problem where the platform aims to incentivize distributed workers to provide high quality and truthful solutions without the ability to verify the solutions. While most prior work assumes that the platform and…

Computer Science and Game Theory · Computer Science 2021-04-12 Chao Huang , Haoran Yu , Jianwei Huang , Randall A. Berry

A number of machine learning (ML) methods have been proposed recently to maximize model predictive accuracy while enforcing notions of group parity or fairness across sub-populations. We propose a desirable property for these procedures,…

Machine Learning · Computer Science 2019-10-08 Ofir Nachum , Heinrich Jiang

We study the voting game where agents' preferences are endogenously decided by the information they receive, and they can collaborate in a group. We show that strategic voting behaviors have a positive impact on leading to the ``correct''…

Computer Science and Game Theory · Computer Science 2023-05-23 Qishen Han , Grant Schoenebeck , Biaoshuai Tao , Lirong Xia

We propose a simple yet effective solution to tackle the often-competing goals of fairness and utility in classification tasks. While fairness ensures that the model's predictions are unbiased and do not discriminate against any particular…

Machine Learning · Computer Science 2023-08-16 Anique Tahir , Lu Cheng , Huan Liu

The distribution of efficient individuals in the economy and the efforts that they will put in if they are hired, there are two important concerns for a technologically advanced firm. wants to open a new branch. The firm does not have…

Computer Science and Game Theory · Computer Science 2025-01-27 Sujata Goala , Mridu Prabal Goswami , Surajit Borkotokey