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Data collecting agents in large networks, such as the electric power system, need to share information (measurements) for estimating the system state in a distributed manner. However, privacy concerns may limit or prevent this exchange…

Information Theory · Computer Science 2015-10-28 E. Veronica Belmega , Lalitha Sankar , H. Vincent Poor

We investigate how asymmetric information affects equilibrium price formation in an economy with many interacting agents. Motivated by a finite-player model with two populations of asymmetrically informed agents, we study its mean-field…

Probability · Mathematics 2026-05-06 Alekos Cecchin , Markus Fischer , Claudio Fontana , Giacomo Lanaro

Self-modification of agents embedded in complex environments is hard to avoid, whether it happens via direct means (e.g. own code modification) or indirectly (e.g. influencing the operator, exploiting bugs or the environment). It has been…

Artificial Intelligence · Computer Science 2021-01-19 Jakub Tětek , Marek Sklenka , Tomáš Gavenčiak

We introduce an interactive market setup with sequential auctions where agents receive variegated signals with a known deadline. The effects of differential information and mutual learning on the allocation of overall profit \& loss (P\&L)…

Mathematical Finance · Quantitative Finance 2016-10-14 N. Serhan Aydin

We study linear-quadratic games of incomplete information with Gaussian uncertainty, where each player's payoff depends on a privately observed type and a common state. The designer observes the state, elicits types, and sells action…

Computer Science and Game Theory · Computer Science 2025-11-04 Alessandro Bonatti , Munther A. Dahleh , Thibaut Horel

We study the problem of designing autonomous agents that can learn to cooperate effectively with a potentially suboptimal partner while having no access to the joint reward function. This problem is modeled as a cooperative episodic…

Machine Learning · Computer Science 2022-06-14 Thomas Kleine Buening , Anne-Marie George , Christos Dimitrakakis

Linear contracts are ubiquitous in practice, yet optimal contract theory often prescribes complex, nonlinear structures. We provide a distributional robustness justification for linear contracts. We study a principal-agent problem where the…

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

We consider a group of agents who can each take an irreversible costly action whose payoff depends on an unknown state. Agents learn about the state from private signals, as well as from past actions of their social network neighbors, which…

Theoretical Economics · Economics 2024-12-11 Wade Hann-Caruthers , Minghao Pan , Omer Tamuz

Two-sided matching markets have long existed to pair agents in the absence of regulated exchanges. A common example is school choice, where a matching mechanism uses student and school preferences to assign students to schools. In such…

Machine Learning · Computer Science 2021-09-17 Stefania Ionescu , Yuhao Du , Kenneth Joseph , Anikó Hannák

This paper investigates the interplay between information diffusion in social networks and its impact on financial markets with an Agent-Based Model (ABM). Agents receive and exchange information about an observable stochastic component of…

General Economics · Economics 2024-12-24 Tommaso Di Francesco , Daniel Torren Peraire

We model endogenous perception of private information in single-agent screening problems, with potential evaluation errors. The agent's evaluation of their type depends on their cognitive state: either attentive (i.e., they correctly…

Theoretical Economics · Economics 2025-03-12 Benjamin Balzer , Benjamin Young

We analyze strategic communication when advice is generated by a reinforcement-learning algorithm rather than by a fully rational sender. Building on the cheap-talk framework of Crawford and Sobel (1982), an advisor adapts its messages…

Theoretical Economics · Economics 2026-02-13 Emilio Calvano , Clemens Possnig , Juha Tolvanen

This paper studies a dynamic model of information acquisition, in which information might be secretly manipulated. A principal must choose between a safe action with known payoff and a risky action with uncertain payoff, favoring the safe…

Theoretical Economics · Economics 2023-04-14 Raphael Boleslavsky

We consider the problem of designing mechanisms that interact with strategic agents through strategic intermediaries (or mediators), and investigate the cost to society due to the mediators' strategic behavior. Selfish agents with private…

Computer Science and Game Theory · Computer Science 2015-01-20 Moshe Babaioff , Moran Feldman , Moshe Tennenholtz

Winners-take-all situations introduce an incentive for agents to diversify their behavior, since doing so will result in splitting an eventual price with fewer people. At the same time, when the payoff of a process depends on a parameter…

Computer Science and Game Theory · Computer Science 2019-06-11 Abel Molina

The main approach to evaluating communication is by assessing how well it facilitates coordination. If two or more individuals can coordinate through communication, it is generally assumed that they understand one another. We investigate…

Artificial Intelligence · Computer Science 2025-09-30 Nikolaos Kondylidis , Anil Yaman , Frank van Harmelen , Erman Acar , Annette ten Teije

Undesired bias afflicts both human and algorithmic decision making, and may be especially prevalent when information processing trade-offs incentivize the use of heuristics. One primary example is \textit{statistical discrimination} --…

An employer contracts with a worker to incentivize efforts whose productivity depends on ability; the worker then enters a market that pays him contingent on ability evaluation. With non-additive monitoring technology, the interdependence…

Theoretical Economics · Economics 2025-07-31 Tan Gan , Hongcheng Li

We consider a hidden-action principal-agent model, in which actions require different amounts of effort, and the agent privately knows his ability that determines his cost of effort. We show that linear contracts admit approximation…

Computer Science and Game Theory · Computer Science 2025-03-05 Tal Alon , Paul Dütting , Yingkai Li , Inbal Talgam-Cohen

This paper presents a multi-agent reinforcement learning algorithm to represent strategic bidding behavior in freight transport markets. Using this algorithm, we investigate whether feasible market equilibriums arise without any central…

Machine Learning · Computer Science 2021-02-19 Wouter van Heeswijk
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