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We study defense strategies against reward poisoning attacks in reinforcement learning. As a threat model, we consider attacks that minimally alter rewards to make the attacker's target policy uniquely optimal under the poisoned rewards,…

Machine Learning · Computer Science 2021-06-22 Kiarash Banihashem , Adish Singla , Goran Radanovic

The decisions that human beings make to allocate time has significant bearing on economic output and to the sustenance of social networks. The time allocation problem motivates our formal analysis of the resource allocation game, where…

Computer Science and Game Theory · Computer Science 2018-08-28 Wei-Chun Lee , Vasilis Livanos , Ruta Mehta , Hari Sundaram

Decision-making individuals are typically either an imitator, who mimics the action of the most successful individual(s), a conformist (or coordinating individual), who chooses an action if enough others have done so, or a nonconformist (or…

Dynamical Systems · Mathematics 2022-02-11 Hien Le , Mohaddeseh Rajaee , Pouria Ramazi

When multiple informative equilibria are possible in a general cheap talk game, how much information can a principal guarantee herself? To answer this question, I define the notion of worst-case implementation-implementation via the worst…

Theoretical Economics · Economics 2026-02-17 Andrei Iakovlev

We consider the problem of designing incentive-compatible, ex-post individually rational (IR) mechanisms for covering problems in the Bayesian setting, where players' types are drawn from an underlying distribution and may be correlated,…

Computer Science and Game Theory · Computer Science 2016-09-30 Hadi Minooei , Chaitanya Swamy

Artificial intelligence and robotic competitions are accompanied by a class of game paradigms in which each player privately commits a strategy to a game system which simulates the game using the collected joint strategy and then returns…

Computer Science and Game Theory · Computer Science 2022-04-28 Rui Yan , Weixian Zhang , Ruiliang Deng , Xiaoming Duan , Zongying Shi , Yisheng Zhong

In dynamic noncooperative games, each player makes conjectures about other players' reactions before choosing a strategy. However, resulting equilibria may be multiple and do not always lead to desirable outcomes. These issues are typically…

Computer Science and Game Theory · Computer Science 2025-11-24 Francesco Morri , Hélène Le Cadre , David Salas , Didier Aussel

We investigate the mechanism design problem faced by a principal who hires \emph{multiple} agents to gather and report costly information. Then, the principal exploits the information to make an informed decision. We model this problem as a…

Computer Science and Game Theory · Computer Science 2023-07-13 Federico Cacciamani , Matteo Castiglioni , Nicola Gatti

Strategic uncertainty complicates policy design in coordination games. To rein in strategic uncertainty, the Planner in this paper connects the problem of policy design to that of equilibrium selection. We characterize the subsidy scheme…

Theoretical Economics · Economics 2023-09-01 Roweno J. R. K. Heijmans

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

In multi-agent reinforcement learning (MARL) and game theory, agents repeatedly interact and revise their strategies as new data arrives, producing a sequence of strategy profiles. This paper studies sequences of strategies satisfying a…

Computer Science and Game Theory · Computer Science 2024-10-02 Bora Yongacoglu , Gürdal Arslan , Lacra Pavel , Serdar Yüksel

We introduce a game of trusted computation in which a sensor equipped with limited computing power leverages a central node to evaluate a specified function over a large dataset, collected over time. We assume that the central computer can…

Computer Science and Game Theory · Computer Science 2016-11-09 Shaunak D. Bopardikar , Alberto Speranzon , Cedric Langbort

Incentivizing the existing participants to invite new participants to join an auction, matching or cooperative game have been extensively studied recently. One common challenge to design such incentive in these games is that the invitees…

Computer Science and Game Theory · Computer Science 2025-02-17 Xinwei Song , Tianyi Yang , Dengji Zhao

Whilst network coordination games and network anti-coordination games have received a considerable amount of attention in the literature, network games with coexisting coordinating and anti-coordinating players are known to exhibit more…

Computer Science and Game Theory · Computer Science 2021-10-26 Laura Arditti , Giacomo Como , Fabio Fagnani , Martina Vanelli

In a combinatorial auction with item bidding, agents participate in multiple single-item second-price auctions at once. As some items might be substitutes, agents need to strategize in order to maximize their utilities. A number of results…

Computer Science and Game Theory · Computer Science 2017-04-17 Paul Dütting , Thomas Kesselheim

In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requirement with the goal of minimizing expected ex post regret,…

Computer Science and Game Theory · Computer Science 2012-08-07 Paul Duetting , Felix Fischer , Pitchayut Jirapinyo , John K. Lai , Benjamin Lubin , David C. Parkes

This work uses Game Theory to study the effectiveness of punishments as an incentive for rational nodes to follow an epidemic dissemination protocol. The dissemination process is modeled as an infinite repetition of a stage game. At the end…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-09-02 Xavier Vilaça , Luís Rodrigues

Stochastic games have become a prevalent framework for studying long-term multi-agent interactions, especially in the context of multi-agent reinforcement learning. In this work, we comprehensively investigate the concept of constant-memory…

Computer Science and Game Theory · Computer Science 2025-10-16 Fengming Zhu , Fangzhen Lin

We examine receiver-optimal mechanisms for aggregating information divided across many biased senders. Each sender privately observes an unconditionally independent signal about an unknown state, so no sender can verify another's report. A…

Theoretical Economics · Economics 2025-08-05 James Best , Daniel Quigley , Maryam Saeedi , Ali Shourideh

In this article, we focus on search algorithms for two-player perfect information games, whose objective is to determine the best possible strategy, and ideally a winning strategy. Unfortunately, some search algorithms for games in the…

Artificial Intelligence · Computer Science 2026-03-26 Quentin Cohen-Solal