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We study a repeated game with payoff externalities and observable actions where two players receive information over time about an underlying payoff-relevant state, and strategically coordinate their actions. Players learn about the true…

Theoretical Economics · Economics 2018-09-05 Pathikrit Basu , Kalyan Chatterjee , Tetsuya Hoshino , Omer Tamuz

Sender-receiver games are simple models of information transmission that provide a formalism to study the evolution of honest signaling and deception between a sender and a receiver. In many practical scenarios, lies often affect groups of…

Physics and Society · Physics 2021-12-01 Aanjaneya Kumar , Sandeep Chowdhary , Valerio Capraro , Matjaz Perc

The problem of reward design examines the interaction between a leader and a follower, where the leader aims to shape the follower's behavior to maximize the leader's payoff by modifying the follower's reward function. Current approaches to…

Optimization and Control · Mathematics 2024-06-10 Shuo Wu , Haoxiang Ma , Jie Fu , Shuo Han

In many two-sided markets, the parties to be matched have incomplete information about their characteristics. We consider the settings where the parties engaged are extremely patient and are interested in long-term partnerships. Hence, once…

Computer Science and Game Theory · Computer Science 2019-08-30 Kartik Ahuja , Mihaela van der Schaar

We propose a new notion of credibility for Bayesian persuasion problems. A disclosure policy is credible if the sender cannot profit from tampering with her messages while keeping the message distribution unchanged. We show that the…

Theoretical Economics · Economics 2022-05-10 Xiao Lin , Ce Liu

We address Bayesian persuasion between a sender and a receiver with state-dependent quadratic cost measures for general classes of distributions. The receiver seeks to make mean-square-error estimate of a state based on a signal sent by the…

Computer Science and Game Theory · Computer Science 2020-09-15 Muhammed O. Sayin , Tamer Basar

A monopolist seller of multiple goods screens a buyer whose type is initially unknown to both but drawn from a commonly known distribution. The buyer privately learns about his type via a signal. We derive the seller's optimal mechanism in…

Theoretical Economics · Economics 2021-05-27 Rahul Deb , Anne-Katrin Roesler

This paper studies optimal consumption and saving decisions under uncertainty about the transition dynamics of the economic environment. We consider a general optimal savings problem in which the exogenous state governing discounting,…

Theoretical Economics · Economics 2026-03-10 Qingyin Ma , Xinxin Zhang

We study the design of contracts that incentivize a researcher to conduct a costly experiment, extending the work of Yoder (2022) from binary states to a general state space. The cost is private information of the researcher. When the…

Theoretical Economics · Economics 2023-07-18 Han Wang

Individuals are often faced with temptations that can lead them astray from long-term goals. We're interested in developing interventions that steer individuals toward making good initial decisions and then maintaining those decisions over…

Machine Learning · Computer Science 2022-03-15 Shruthi Sukumar , Adrian F. Ward , Camden Elliott-Williams , Shabnam Hakimi , Michael C. Mozer

We study learning dynamics induced by strategic agents who repeatedly play a game with an unknown payoff-relevant parameter. In this dynamics, a belief estimate of the parameter is repeatedly updated given players' strategies and realized…

Computer Science and Game Theory · Computer Science 2021-09-06 Manxi Wu , Saurabh Amin , Asuman Ozdaglar

How do incentive levels affect strategic behaviour? We address this with an experiment that separately identifies own- and opponent-incentive effects in two dominance-solvable games that differ in strategic complexity. Higher own incentives…

Theoretical Economics · Economics 2026-03-30 Teresa Esteban-Casanelles , Duarte Gonçalves

The Bayesian persuasion paradigm of strategic communication models interaction between a privately-informed agent, called the sender, and an ignorant but rational agent, called the receiver. The goal is typically to design a (near-)optimal…

Computer Science and Game Theory · Computer Science 2021-06-21 Ronen Gradwohl , Niklas Hahn , Martin Hoefer , Rann Smorodinsky

Game theory serves as a powerful tool for distributed optimization in multi-agent systems in different applications. In this paper we consider multi-agent systems that can be modeled by means of potential games whose potential function…

Optimization and Control · Mathematics 2018-04-13 Tatiana Tatarenko

Spatial evolutionary games provide a valuable framework for elucidating the emergence and maintenance of cooperative behavior. However, most previous studies assume that individuals are profiteers and neglect to consider the effects of…

Computer Science and Game Theory · Computer Science 2025-11-25 Bin Pi , Minyu Feng , Liang-Jian Deng

Recent literature highlights the advantages of implementing social rules via dynamic game forms. We characterize when truth-telling remains a dominant strategy in gradual mechanisms implementing strategy-proof social rules, where agents…

Theoretical Economics · Economics 2025-03-27 Wenqian Wang , Zhiwen Zheng

Consider a set of agents who play a network game repeatedly. Agents may not know the network. They may even be unaware that they are interacting with other agents in a network. Possibly, they just understand that their payoffs depend on an…

Theoretical Economics · Economics 2022-07-26 Pierpaolo Battigalli , Fabrizio Panebianco , Paolo Pin

Consider a market where a seller owns an item for sale and a buyer wants to purchase it. Each player has private information, known as their type. It can be costly and difficult for the players to reach an agreement through direct…

Computer Science and Game Theory · Computer Science 2024-10-29 Zhikang Fan , Weiran Shen

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