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In many real-world scenarios, experts must convey complex information with limited message capacity. This paper explores how the availability of messages influences an expert's persuasive ability. We develop a geometric representation of…

Theoretical Economics · Economics 2024-05-09 Yunus C. Aybas , Eray Turkel

Motivated by information sharing in online platforms, we study repeated persuasion between a sender and a stream of receivers where at each time, the sender observes a payoff-relevant state drawn independently and identically from an…

Computer Science and Game Theory · Computer Science 2024-05-06 You Zu , Krishnamurthy Iyer , Haifeng Xu

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

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 introduce a stochastic principal-agent model. A principal and an agent interact in a stochastic environment, each privy to observations about the state not available to the other. The principal has the power of commitment, both to elicit…

Computer Science and Game Theory · Computer Science 2024-09-13 Jiarui Gan , Rupak Majumdar , Debmalya Mandal , Goran Radanovic

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents…

Machine Learning · Computer Science 2014-08-12 Aristide Tossou , Christos Dimitrakakis

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents…

Machine Learning · Statistics 2013-07-16 Aristide C. Y. Tossou , Christos Dimitrakakis

Bayesian inference has theoretical attractions as a principled framework for reasoning about beliefs. However, the motivations of Bayesian inference which claim it to be the only 'rational' kind of reasoning do not apply in practice. They…

Machine Learning · Statistics 2022-11-14 Sebastian Farquhar

We study strategic information transmission in a hierarchical setting where information gets transmitted through a chain of agents up to a decision maker whose action is of importance to every agent. This situation could arise whenever an…

Theoretical Economics · Economics 2022-07-14 Majid Mahzoon

Peer grading systems aggregate noisy reports from multiple students to approximate a true grade as closely as possible. Most current systems either take the mean or median of reported grades; others aim to estimate students' grading…

Artificial Intelligence · Computer Science 2022-12-05 Hedayat Zarkoob , Greg d'Eon , Lena Podina , Kevin Leyton-Brown

Bayesian models of group learning are studied in Economics since the 1970s. and more recently in computational linguistics. The models from Economics postulate that agents maximize utility in their communication and actions. The Economics…

Statistics Theory · Mathematics 2023-08-10 Yash Deshpande , Elchanan Mossel , Youngtak Sohn

This paper presents a plausible reasoning system to illustrate some broad issues in knowledge representation: dualities between different reasoning forms, the difficulty of unifying complementary reasoning styles, and the approximate nature…

Artificial Intelligence · Computer Science 2013-03-26 Wray L. Buntine

We investigate the algorithmic problem of selling information to agents who face a decision-making problem under uncertainty. We adopt the model recently proposed by Bergemann et al. [BBS18], in which information is revealed through…

Computer Science and Game Theory · Computer Science 2020-12-24 Yang Cai , Grigoris Velegkas

In an empirical study of persuasion, researchers often use a binary instrument to encourage individuals to consume information and take some action. We show that, with a binary Imbens-Angrist instrumental variable model and the monotone…

Econometrics · Economics 2025-07-02 Zeyang Yu

The hidden-action model captures a fundamental problem of principal-agent theory and provides an optimal sharing rule when only the outcome but not the effort can be observed. However, the hidden-action model builds on various explicit and…

General Economics · Economics 2020-04-15 Stephan Leitner , Friederike Wall

We study a setting where a group of agents, each receiving partially informative private signals, seek to collaboratively learn the true underlying state of the world (from a finite set of hypotheses) that generates their joint observation…

Systems and Control · Electrical Eng. & Systems 2019-07-09 Aritra Mitra , John A. Richards , Shreyas Sundaram

Most of agents that learn policy for tasks with reinforcement learning (RL) lack the ability to communicate with people, which makes human-agent collaboration challenging. We believe that, in order for RL agents to comprehend utterances…

Artificial Intelligence · Computer Science 2018-10-15 Yosuke Fukuchi , Masahiko Osawa , Hiroshi Yamakawa , Tatsuji Takahashi , Michita Imai

A principal and an agent can launch a project under unanimous consent. Their individual payoffs from the project depend on an underlying state, and the agent privately knows his own preference. The principal can conduct a test to learn…

Theoretical Economics · Economics 2026-02-06 Yingkai Li , Boli Xu

Previous work has showcased the intriguing capabilities of Large Language Models (LLMs) in instruction-following and rhetorical fluency. However, systematic exploration of their dual capabilities to autonomously persuade and resist…

Computation and Language · Computer Science 2025-06-10 Tianjie Ju , Yujia Chen , Hao Fei , Mong-Li Lee , Wynne Hsu , Pengzhou Cheng , Zongru Wu , Zhuosheng Zhang , Gongshen Liu

Issue salience is a major determinant in voters' decisions. Candidates and political parties campaign to shift salience to their advantage - a process termed priming. We study the dynamics, strategies and equilibria of campaign spending for…

Computer Science and Game Theory · Computer Science 2024-12-30 Jonathan Shaki , Yonatan Aumann , Sarit Kraus