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I study a social learning model in which the object to learn is a strategic player's endogenous actions rather than an exogenous state. A patient seller faces a sequence of buyers and decides whether to build a reputation for supplying high…

Theoretical Economics · Economics 2020-11-03 Harry Pei

We analyze a nonlinear pricing model where the seller controls both product pricing (screening) and buyer information about their own values (persuasion). We prove that the optimal mechanism always consists of finitely many signals and…

Theoretical Economics · Economics 2025-03-11 Dirk Bergemann , Tibor Heumann , Stephen Morris

An information theoretic privacy mechanism design problem for two scenarios is studied where the private data is either hidden or observable. In each scenario, privacy leakage constraints are considered using two different measures. In…

Information Theory · Computer Science 2022-05-11 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

We study the optimal referral strategy of a seller and its relationship with the type of communication channels among consumers. The seller faces a partially uninformed population of consumers, interconnected through a directed social…

Physics and Society · Physics 2018-12-27 Elias Carroni , Paolo Pin , Simone Righi

Strategic information is valuable either by remaining private (for instance if it is sensitive) or, on the other hand, by being used publicly to increase some utility. These two objectives are antagonistic and leaking this information might…

Machine Learning · Statistics 2020-03-03 Etienne Boursier , Vianney Perchet

We study a class of finite-action disclosure games in which the sender's preferences are state-independent and the receiver's optimal action depends only on the expected state. While receiver-preferred equilibria in these games involve full…

Theoretical Economics · Economics 2026-05-06 Denis Shishkin , Maria Titova , Kun Zhang

This paper examines competitive information disclosure in search markets with a mix of savvy consumers, who search costlessly, and inexperienced consumers, who face positive search costs. Savvy consumers incentivize truthful disclosure;…

Theoretical Economics · Economics 2025-06-11 Raphael Boleslavsky , Silvana Krasteva

We study the notion of informedness in a client-consultant setting. Using a software simulator, we examine the extent to which it pays off for consultants to provide their clients with advice that is well-informed, or with advice that is…

Artificial Intelligence · Computer Science 2009-09-07 Eugen Staab , Martin Caminada

We consider a setting where $n$ buyers, with combinatorial preferences over $m$ items, and a seller, running a priority-based allocation mechanism, repeatedly interact. Our goal, from observing limited information about the results of these…

Computer Science and Game Theory · Computer Science 2014-08-29 Avrim Blum , Yishay Mansour , Jamie Morgenstern

Data buyers compete in a game of incomplete information about which a single data seller owns some payoff-relevant information. The seller faces a joint information- and mechanism-design problem: deciding which information to sell, while…

Computer Science and Game Theory · Computer Science 2024-11-18 Alessandro Bonatti , Munther Dahleh , Thibaut Horel , Amir Nouripour

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

Recommender systems have become a pervasive part of our daily online experience, and are one of the most widely used applications of artificial intelligence and machine learning. Therefore, regulations and requirements for trustworthy…

Information Retrieval · Computer Science 2024-07-01 Dominik Kowald

I consider decision-making constrained by considerations of morality, rationality, or other virtues. The decision maker (DM) has a true preference over outcomes, but feels compelled to choose among outcomes that are top-ranked by some…

Theoretical Economics · Economics 2020-03-17 Sarah Ridout

Algorithmic transparency entails exposing system properties to various stakeholders for purposes that include understanding, improving, and contesting predictions. Until now, most research into algorithmic transparency has predominantly…

We propose a model of causal persuasion, in which a sender selectively discloses a set of variables together with their true joint distribution and proposes a subjective causal model that binds them. A receiver is persuaded by this model…

Theoretical Economics · Economics 2026-05-04 Anastasia Burkovskaya , Egor Starkov

A policymaker discloses public information to interacting agents who also acquire costly private information. More precise public information reduces the precision and cost of acquired private information. Considering this effect, what…

Theoretical Economics · Economics 2022-04-08 Takashi Ui

Many auction settings implicitly or explicitly require that bidders are treated equally ex-ante. This may be because discrimination is philosophically or legally impermissible, or because it is practically difficult to implement or…

Computer Science and Game Theory · Computer Science 2014-11-06 Christos Tzamos , Christopher A. Wilkens

The disposition effect describes investors' irrational behavior of selling profitable assets too soon while holding onto losing assets for too long. This study examines the impact of transparency at the firm level on the disposition effect…

General Finance · Quantitative Finance 2026-05-11 Siliu Chen , Fei Ren

Transparency and security are both central to Responsible AI, but they may conflict in adversarial settings. We investigate the strategic effect of transparency for agents through the lens of transferable adversarial example attacks. In…

Machine Learning · Computer Science 2025-11-18 Lucas Fenaux , Christopher Srinivasa , Florian Kerschbaum

Recommender systems leverage user demographic information, such as age, gender, etc., to personalize recommendations and better place their targeted ads. Oftentimes, users do not volunteer this information due to privacy concerns, or due to…

Machine Learning · Computer Science 2014-08-01 Smriti Bhagat , Udi Weinsberg , Stratis Ioannidis , Nina Taft
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