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It is shown in recent studies that in a Stackelberg game the follower can manipulate the leader by deviating from their true best-response behavior. Such manipulations are computationally tractable and can be highly beneficial for the…

Computer Science and Game Theory · Computer Science 2023-02-28 Yurong Chen , Xiaotie Deng , Jiarui Gan , Yuhao Li

Recent results in the ML community have revealed that learning algorithms used to compute the optimal strategy for the leader to commit to in a Stackelberg game, are susceptible to manipulation by the follower. Such a learning algorithm…

Computer Science and Game Theory · Computer Science 2022-09-12 Georgios Birmpas , Jiarui Gan , Alexandros Hollender , Francisco J. Marmolejo-Cossío , Ninad Rajgopal , Alexandros A. Voudouris

Information uncertainty is one of the major challenges facing applications of game theory. In the context of Stackelberg games, various approaches have been proposed to deal with the leader's incomplete knowledge about the follower's…

Computer Science and Game Theory · Computer Science 2019-05-21 Jiarui Gan , Haifeng Xu , Qingyu Guo , Long Tran-Thanh , Zinovi Rabinovich , Michael Wooldridge

We study payoff manipulation in repeated multi-objective Stackelberg games, where a leader may strategically influence a follower's deterministic best response, e.g., by offering a share of their own payoff. We assume that the follower's…

Computer Science and Game Theory · Computer Science 2025-08-27 Phurinut Srisawad , Juergen Branke , Long Tran-Thanh

A valuation for a player in a game in extensive form is an assignment of numeric values to the players moves. The valuation reflects the desirability moves. We assume a myopic player, who chooses a move with the highest valuation.…

Machine Learning · Computer Science 2007-05-23 Philippe Jehiel , Dov Samet

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

I study a repeated game in which a patient player (e.g., a seller) wants to win the trust of some myopic opponents (e.g., buyers) but can strictly benefit from betraying them. Her benefit from betrayal is strictly positive and is her…

Theoretical Economics · Economics 2020-06-16 Harry Pei

A Stackelberg game is played between a leader and a follower. The leader first chooses an action, then the follower plays his best response. The goal of the leader is to pick the action that will maximize his payoff given the follower's…

Data Structures and Algorithms · Computer Science 2015-11-19 Aaron Roth , Jonathan Ullman , Zhiwei Steven Wu

We study an online learning problem in general-sum Stackelberg games, where players act in a decentralized and strategic manner. We study two settings depending on the type of information for the follower: (1) the limited information…

Machine Learning · Computer Science 2025-05-06 Yaolong Yu , Haipeng Chen

We study games in which a leader makes a single commitment, and then multiple followers (each with a different utility function) respond. In particular, we study ambiguous commitment strategies in these games, in which the leader may commit…

Computer Science and Game Theory · Computer Science 2024-09-10 Natalie Collina , Rabanus Derr , Aaron Roth

Repeated game has long been the touchstone model for agents' long-run relationships. Previous results suggest that it is particularly difficult for a repeated game player to exert an autocratic control on the payoffs since they are jointly…

Computer Science and Game Theory · Computer Science 2018-07-19 Dong Hao , Kai Li , Tao Zhou

In Stackelberg security games when information about the attacker's payoffs is uncertain, algorithms have been proposed to learn the optimal defender commitment by interacting with the attacker and observing their best responses. In this…

Computer Science and Game Theory · Computer Science 2019-11-01 Jiarui Gan , Qingyu Guo , Long Tran-Thanh , Bo An , Michael Wooldridge

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 extensive-form bandit problem, where on each trial the learner (a user coordinated by a server) plays an extensive-form game against an oblivious adversary, observing the information sets it finds itself in as well as the…

Cryptography and Security · Computer Science 2026-05-08 Stephen Pasteris , Rahul Savani , Theodore Turocy

In repeated interactions between individuals, we do not expect that exactly the same situation will occur from one time to another. Contrary to what is common in models of repeated games in the literature, most real situations may differ a…

Populations and Evolution · Quantitative Biology 2007-05-23 Anders Eriksson , Kristian Lindgren

Originating in evolutionary game theory, the class of "zero-determinant" strategies enables a player to unilaterally enforce linear payoff relationships in simple repeated games. An upshot of this kind of payoff constraint is that it can…

Theoretical Economics · Economics 2025-11-26 Nikos Dimou , Alex McAvoy

In imperfect information games (e.g. Bridge, Skat, Poker), one of the fundamental considerations is to infer the missing information while at the same time avoiding the disclosure of private information. Disregarding the issue of protecting…

Artificial Intelligence · Computer Science 2024-05-24 Jérôme Arjonilla , Abdallah Saffidine , Tristan Cazenave

Gameplay under various forms of uncertainty has been widely studied. Feldman et al. (2010) studied a particularly low-information setting in which one observes the opponent's actions but no payoffs, not even one's own, and introduced an…

Computer Science and Game Theory · Computer Science 2024-04-02 Avrim Blum , Melissa Dutz

We study reputation formation where a long-run player repeatedly observes private signals and takes actions. Short-run players observe the long-run player's past actions but not her past signals. The long-run player can thus develop a…

Theoretical Economics · Economics 2025-07-22 Daniel Luo , Alexander Wolitzky

We study the long-term behavior of the fictitious play process in repeated extensive-form games of imperfect information with perfect recall. Each player maintains incorrect beliefs that the moves at all information sets, except the one at…

Computer Science and Game Theory · Computer Science 2025-04-28 Jason Castiglione , Gürdal Arslan
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