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Related papers: Learning to Persuade a Biased Receiver

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A persuasion policy successfully persuades an agent to pick a particular action only if the information is designed in a manner that convinces the agent that it is in their best interest to pick that action. Thus, it is natural to ask, what…

Computer Science and Game Theory · Computer Science 2024-08-27 Reema Deori , Ankur A. Kulkarni

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

We frame dynamic persuasion in a partial observation stochastic control Leader-Follower game with an ergodic criterion. The Receiver controls the dynamics of a multidimensional unobserved state process. Information is provided to the…

Optimization and Control · Mathematics 2025-06-23 René Aïd , Ofelia Bonesini , Giorgia Callegaro , Luciano Campi

Appropriate decisions depend on information gathered beforehand, yet such information is often obtained through intermediaries with biased preferences. Motivated by settings such as testing and recertification in organ transplantation, we…

Theoretical Economics · Economics 2026-02-17 Andres Espitia , Edwin Muñoz-Rodríguez

Perceptual estimates exhibit a reversal in bias depending on uncertainty: they shift toward prior expectations under high stimulus noise, but away from them when sensory noise dominates. The normative framework of a Bayesian observer model…

Neurons and Cognition · Quantitative Biology 2025-10-16 Hyun-Jun Jeon , Hansol Choi , Oh-Sang Kwon

We study the problem of online learning (OL) from revealed preferences: a learner wishes to learn a non-strategic agent's private utility function through observing the agent's utility-maximizing actions in a changing environment. We adopt…

Optimization and Control · Mathematics 2021-06-07 Violet Xinying Chen , Fatma Kılınç-Karzan

We present a new recommendation setting for picking out two items from a given set to be highlighted to a user, based on contextual input. These two items are presented to a user who chooses one of them, possibly stochastically, with a bias…

Machine Learning · Computer Science 2016-01-26 Daniel Barsky , Koby Crammer

What we discover and see online, and consequently our opinions and decisions, are becoming increasingly affected by automated machine learned predictions. Similarly, the predictive accuracy of learning machines heavily depends on the…

Information Retrieval · Computer Science 2020-01-15 Sami Khenissi , Olfa Nasraoui

We study the problem of online learning with primary and secondary losses. For example, a recruiter making decisions of which job applicants to hire might weigh false positives and false negatives equally (the primary loss) but the…

Machine Learning · Computer Science 2020-10-29 Avrim Blum , Han Shao

Bayesian persuasion is the study of information sharing policies among strategic agents. A prime example is signaling in online ad auctions: what information should a platform signal to an advertiser regarding a user when selling the…

Computer Science and Game Theory · Computer Science 2021-04-13 Yakov Babichenko , Inbal Talgam-Cohen , Konstantin Zabarnyi

We study online linear regression problems in a distributed setting, where the data is spread over a network. In each round, each network node proposes a linear predictor, with the objective of fitting the \emph{network-wide} data. It then…

Machine Learning · Computer Science 2019-02-14 Deming Yuan , Alexandre Proutiere , Guodong Shi

We consider the problem of online learning with non-convex losses. In terms of feedback, we assume that the learner observes - or otherwise constructs - an inexact model for the loss function encountered at each stage, and we propose a…

Machine Learning · Computer Science 2020-10-19 Amélie Héliou , Matthieu Martin , Panayotis Mertikopoulos , Thibaud Rahier

Policy learning algorithms are widely used in areas such as personalized medicine and advertising to develop individualized treatment regimes. However, most methods force a decision even when predictions are uncertain, which is risky in…

Machine Learning · Computer Science 2026-01-30 Ayush Sawarni , Jikai Jin , Justin Whitehouse , Vasilis Syrgkanis

An agent acquires information dynamically until her belief about a binary state reaches an upper or lower threshold. She can choose any signal process subject to a constraint on the rate of entropy reduction. Strategies are ordered by "time…

Theoretical Economics · Economics 2024-08-23 Daniel Chen , Weijie Zhong

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

How does one test empirically the hypothesis that a decision maker (DM) is being influenced by information via Bayesian persuasion? In this paper, I consider a DM whose state-dependent preferences are known to an analyst, who sees the…

Theoretical Economics · Economics 2026-05-13 Jeffrey Mensch

We study dynamic pricing where a seller repeatedly interacts with a strategic, non-myopic buyer who has a fixed private valuation and discounts future utility. Prior work focused exclusively on posted-price mechanisms, which only extract…

Computer Science and Game Theory · Computer Science 2026-04-28 Shiliang Zuo

In bipartite matching problems, agents on two sides of a graph want to be paired according to their preferences. The stability of a matching depends on these preferences, which in uncertain environments also reflect agents' beliefs about…

Computer Science and Game Theory · Computer Science 2025-11-10 Jonathan Shaki , Jiarui Gan , Sarit Kraus

In the persuasion model, apart from a few special cases, comparative statics has been an open question. We answer it, delineating which shifts of the sender's interim payoff lead her optimally to choose a more informative signal. Our first…

Theoretical Economics · Economics 2025-11-26 Gregorio Curello , Ludvig Sinander

Consider a persuasion game where both the sender and receiver are ambiguity averse with maxmin expected utility (MEU) preferences and the sender can choose an ambiguous information structure. This paper analyzes the game in an ex-ante…

Theoretical Economics · Economics 2026-02-12 Xiaoyu Cheng
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