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We suggest a general method for inferring players' values from their actions in repeated games. The method extends and improves upon the recent suggestion of (Nekipelov et al., EC 2015) and is based on the assumption that players are more…

Computer Science and Game Theory · Computer Science 2017-02-17 Noam Nisan , Gali Noti

Nowadays, rating systems play a crucial role in the attraction of customers for different services. However, as it is difficult to detect a fake rating, attackers can potentially impact the rating's aggregated score unfairly. This malicious…

Computer Science and Game Theory · Computer Science 2022-08-05 Iman Vakilinia , Peyman Faizian , Mohammad Mahdi Khalili

We study the problem of multi-agent multi-armed bandits with adversarial corruption in a heterogeneous setting, where each agent accesses a subset of arms. The adversary can corrupt the reward observations for all agents. Agents share these…

Machine Learning · Computer Science 2024-11-14 Fatemeh Ghaffari , Xuchuang Wang , Jinhang Zuo , Mohammad Hajiesmaili

The AI4GCC competition presents a bold step forward in the direction of integrating machine learning with traditional economic policy analysis. Below, we highlight two potential areas for improvement that could enhance the competition's…

Artificial Intelligence · Computer Science 2023-08-11 Marco Jiralerspong , Gauthier Gidel

As machine learning algorithms increasingly influence critical decision making in different application areas, understanding human strategic behavior in response to these systems becomes vital. We explore individuals' choice between…

Machine Learning · Computer Science 2026-03-17 Sura Alhanouti , Parinaz Naghizadeh

To regulate a social system comprised of self-interested agents, economic incentives are often required to induce a desirable outcome. This incentive design problem naturally possesses a bilevel structure, in which a designer modifies the…

Computer Science and Game Theory · Computer Science 2022-10-14 Boyi Liu , Jiayang Li , Zhuoran Yang , Hoi-To Wai , Mingyi Hong , Yu Marco Nie , Zhaoran Wang

We consider the setting of iterative learning control, or model-based policy learning in the presence of uncertain, time-varying dynamics. In this setting, we propose a new performance metric, planning regret, which replaces the standard…

Machine Learning · Computer Science 2021-03-01 Naman Agarwal , Elad Hazan , Anirudha Majumdar , Karan Singh

We study the game redesign problem in which an external designer has the ability to change the payoff function in each round, but incurs a design cost for deviating from the original game. The players apply no-regret learning algorithms to…

Computer Science and Game Theory · Computer Science 2021-10-25 Yuzhe Ma , Young Wu , Xiaojin Zhu

Sabotage games are played on a dynamic graph, in which one agent, called a runner, attempts to reach a goal state, while being obstructed by a demon who at each round removes an edge from the graph. Sabotage modal logic was proposed to…

Logic in Computer Science · Computer Science 2026-04-07 Nina Gierasimczuk , Katrine B. P. Thoft

We study a problem where a group of agents has to decide how a joint reward should be shared among them. We focus on settings where the share that each agent receives depends on the subjective opinions of its peers concerning that agent's…

Computer Science and Game Theory · Computer Science 2013-05-23 Arthur Carvalho , Kate Larson

A $p$-beauty contest is a wide class of games of guessing the most popular strategy among other players. In particular, guessing a fraction of a mean of numbers chosen by all players is a classic behavioral experiment designed to test…

General Economics · Economics 2025-10-23 Iuliia Alekseenko , Dmitry Dagaev , Sofia Paklina , Petr Parshakov

We demonstrate the usefulness of adding delay to infinite games with quantitative winning conditions. In a delay game, one of the players may delay her moves to obtain a lookahead on her opponent's moves. We show that determining the winner…

Computer Science and Game Theory · Computer Science 2017-04-21 Martin Zimmermann

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

Making an informed decision -- for example, when choosing a career or housing -- requires knowledge about the available options. Such knowledge is generally acquired through costly trial and error, but this learning process can be disrupted…

Machine Learning · Computer Science 2022-04-15 Sarah H. Cen , Devavrat Shah

We study game-theoretic models for capturing participation in blockchain systems. Permissionless blockchains can be naturally viewed as games, where a set of potentially interested users is faced with the dilemma of whether to engage with…

Computer Science and Game Theory · Computer Science 2023-12-06 Pyrros Chaidos , Aggelos Kiayias , Evangelos Markakis

Game dynamics, which describe how agents' strategies evolve over time based on past interactions, can exhibit a variety of undesirable behaviours including convergence to suboptimal equilibria, cycling, and chaos. While central planners can…

Systems and Control · Electrical Eng. & Systems 2025-11-25 Ilayda Canyakmaz , Iosif Sakos , Wayne Lin , Antonios Varvitsiotis , Georgios Piliouras

We study the problem of agent selection in causal strategic learning under multiple decision makers and address two key challenges that come with it. Firstly, while much of prior work focuses on studying a fixed pool of agents that remains…

Artificial Intelligence · Computer Science 2024-02-06 Kiet Q. H. Vo , Muneeb Aadil , Siu Lun Chau , Krikamol Muandet

We study the asymptotic behavior of the ratio of total return (or total profit) to total amount bet in a casino game. While the limit is well understood when the sequence of wagers is independent and identically distributed, here we…

Probability · Mathematics 2025-12-25 S. N. Ethier , L. Stefanello

This thesis considers sequential decision problems, where the loss/reward incurred by selecting an action may not be inferred from observed feedback. A major part of this thesis focuses on the unsupervised sequential selection problem,…

Machine Learning · Computer Science 2023-01-30 Arun Verma

Tanking, the act of deliberately dropping points or losing a game in order to gain some other advantage, is usually seen as being against the spirit of sports. It can be even more serious if playing a draw is a (weakly) dominant strategy…

Physics and Society · Physics 2020-08-26 László Csató