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Related papers: Axiomatic Foundations of Bayesian Persuasion

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Classical Bayesian persuasion studies how a sender influences receivers through carefully designed signaling policies within a single strategic interaction. In many real-world environments, such interactions are repeated across multiple…

Computer Science and Game Theory · Computer Science 2026-03-24 Ata Poyraz Turna , Asrin Efe Yorulmaz , Tamer Başar

We study how a decision-maker can acquire more information from an agent by reducing her own ability to observe what the agent transmits. In a large class of binary-action games, opacity design is just as good as full commitment to actions…

Theoretical Economics · Economics 2024-02-07 Mark Whitmeyer

We consider a multi-agent delegation mechanism without money. In our model, given a set of agents, each agent has a fixed number of solutions which is exogenous to the mechanism, and privately sends a signal, e.g., a subset of solutions, to…

Computer Science and Game Theory · Computer Science 2023-05-23 MohammadTaghi Hajiaghayi , Keivan Rezaei , Suho Shin

We study the use of Bayesian persuasion (i.e., strategic use of information disclosure/signaling) in endogenous team formation. This is an important consideration in settings such as crowdsourcing competitions, open science challenges and…

Computer Science and Game Theory · Computer Science 2019-10-03 Chamsi Hssaine , Siddhartha Banerjee

In recent studies of political decision-making, apparently anomalous behavior has been observed on the part of voters, in which negative information about a candidate strengthens, rather than weakens, a prior positive opinion about the…

Artificial Intelligence · Computer Science 2013-06-12 William W. Cohen , David P. Redlawsk , Douglas Pierce

Common sense suggests that when individuals explain why they believe something, we can arrive at more accurate conclusions than when they simply state what they believe. Yet, there is no known mechanism that provides incentives to elicit…

Computer Science and Game Theory · Computer Science 2025-02-20 Siddarth Srinivasan , Ezra Karger , Michiel Bakker , Yiling Chen

We consider a dynamic Bayesian persuasion setting where a single long-lived sender persuades a stream of ``short-lived'' agents (receivers) by sharing information about a payoff-relevant state. The state transitions are Markovian and the…

Computer Science and Game Theory · Computer Science 2023-07-17 Krishnamurthy Iyer , Haifeng Xu , You Zu

We study the robustness of Bayesian persuasion to uncertainty about the receiver's preferences. We analyze two conceptually distinct notions: continuity, in which only the modeler lacks precise knowledge, but where the model's predictions…

Theoretical Economics · Economics 2026-05-28 Ronen Gradwohl , Fengming Hu , Rann Smorodinsky

In a game of persuasion with evidence, a sender has private information. By presenting evidence on the information, the sender wishes to persuade a receiver to take a single action (e.g., hire a job candidate, or convict a defendant). The…

Computer Science and Game Theory · Computer Science 2024-09-10 Martin Hoefer , Pasin Manurangsi , Alexandros Psomas

Decision-makers in high-stakes selection processes often face a fundamental choice: whether to make decisions themselves or to delegate authority to another entity whose incentives may only be partially aligned with their own. Such…

Computers and Society · Computer Science 2026-01-16 Benjamin Fish , Diptangshu Sen , Juba Ziani

We study hidden-action principal-agent problems in which a principal commits to an outcome-dependent payment scheme (called contract) so as to incentivize the agent to take a costly, unobservable action leading to favorable outcomes. In…

Computer Science and Game Theory · Computer Science 2022-08-18 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

In this paper the problem of learning appropriate bias for an environment of related tasks is examined from a Bayesian perspective. The environment of related tasks is shown to be naturally modelled by the concept of an {\em objective}…

Machine Learning · Computer Science 2019-11-15 Jonathan Baxter

We consider a dynamic model of Bayesian persuasion in which information takes time and is costly for the sender to generate and for the receiver to process, and neither player can commit to their future actions. Persuasion may totally…

Theoretical Economics · Economics 2022-10-03 Yeon-Koo Che , Kyungmin Kim , Konrad Mierendorff

Bayesian observer and actor models have provided normative explanations for many behavioral phenomena in perception, sensorimotor control, and other areas of cognitive science and neuroscience. They attribute behavioral variability and…

Machine Learning · Computer Science 2025-02-03 Dominik Straub , Tobias F. Niehues , Jan Peters , Constantin A. Rothkopf

We focus on the scenario in which an agent can exploit his information advantage to manipulate the outcome of an election. In particular, we study district-based elections with two candidates, in which the winner of the election is the…

Computer Science and Game Theory · Computer Science 2020-12-11 Matteo Castiglioni , Nicola Gatti

Autonomous agents operating in sequential decision-making tasks under uncertainty can benefit from external action suggestions, which provide valuable guidance but inherently vary in reliability. Existing methods for incorporating such…

Artificial Intelligence · Computer Science 2026-05-26 Dylan M. Asmar , Mykel J. Kochenderfer

Prominent opinion formation models such as the one by Friedkin and Johnsen (FJ) concentrate on the effects of peer pressure on public opinions. In practice, opinion formation is also based on information about the state of the world and…

Computer Science and Game Theory · Computer Science 2025-09-10 Martin Hoefer , Tim Koglin , Tolga Tel

We study a model of consensus decision making, in which a finite group of Bayesian agents has to choose between one of two courses of action. Each member of the group has a private and independent signal at his or her disposal, giving some…

Statistics Theory · Mathematics 2018-04-24 Elchanan Mossel , Omer Tamuz

A sender first publicly commits to an experiment and then can privately run additional experiments and selectively disclose their outcomes to a receiver. The sender has private information about the maximal number of additional experiments…

Theoretical Economics · Economics 2026-01-12 Yifan Dai , Drew Fudenberg , Harry Pei

Whereas acausal Bayesian networks represent probabilistic independence, causal Bayesian networks represent causal relationships. In this paper, we examine Bayesian methods for learning both types of networks. Bayesian methods for learning…

Artificial Intelligence · Computer Science 2015-05-19 David Heckerman