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In a Stackelberg game, a leader commits to a randomized strategy, and a follower chooses their best strategy in response. We consider an extension of a standard Stackelberg game, called a discrete-time dynamic Stackelberg game, that has an…

Computer Science and Game Theory · Computer Science 2022-02-11 Niklas Lauffer , Mahsa Ghasemi , Abolfazl Hashemi , Yagiz Savas , Ufuk Topcu

This paper introduces the new concept of (follower) satisfaction in Stackelberg games and compares the standard Stackelberg game with its satisfaction version. Simulation results are presented which suggest that the follower adopting…

Computer Science and Game Theory · Computer Science 2024-08-22 Langford White , Duong Nguyen , Hung Nguyen

We study the problem of online learning in Stackelberg games with side information between a leader and a sequence of followers. In every round the leader observes contextual information and commits to a mixed strategy, after which the…

Machine Learning · Computer Science 2026-05-05 Maria-Florina Balcan , Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Keegan Harris , Zhiwei Steven Wu

We study online learning in Bayesian Stackelberg games, where a leader repeatedly interacts with a follower whose unknown private type is independently drawn at each round from an unknown probability distribution. The goal is to design…

Computer Science and Game Theory · Computer Science 2026-02-03 Matteo Bollini , Francesco Bacchiocchi , Samuel Coutts , Matteo Castiglioni , Alberto Marchesi

The behavior of no-regret learning algorithms is well understood in two-player min-max (i.e, zero-sum) games. In this paper, we investigate the behavior of no-regret learning in min-max games with dependent strategy sets, where the strategy…

Computer Science and Game Theory · Computer Science 2022-04-15 Denizalp Goktas , Jiayi Zhao , Amy Greenwald

We study a continuous-time stochastic Stackelberg game in which a leader seeks to accomplish a primary objective while inferring a hidden parameter of a rational follower. The follower solves an entropy-regularized tracking problem and…

Optimization and Control · Mathematics 2025-10-08 Ruimeng Hu , Daniel Ralston , Xu Yang , Haosheng Zhou

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 extend the formalism of Conjectural Variations games to Stackelberg games involving multiple leaders and a single follower. To solve these nonconvex games, a common assumption is that the leaders compute their strategies having perfect…

Computer Science and Game Theory · Computer Science 2025-07-24 Francesco Morri , Hélène Le Cadre , Luce Brotcorne

We consider the problem of efficiently learning to play single-leader multi-follower Stackelberg games when the leader lacks knowledge of the lower-level game. Such games arise in hierarchical decision-making problems involving…

Systems and Control · Electrical Eng. & Systems 2025-12-11 Anna Maddux , Marko Maljkovic , Nikolas Geroliminis , Maryam Kamgarpour

We study Stackelberg equilibria in finitely repeated games, where the leader commits to a strategy that picks actions in each round and can be adaptive to the history of play (i.e. they commit to an algorithm). In particular, we study…

Computer Science and Game Theory · Computer Science 2024-03-08 Natalie Collina , Eshwar Ram Arunachaleswaran , Michael Kearns

In increasingly different contexts, it happens that a human player has to interact with artificial players who make decisions following decision-making algorithms. How should the human player play against these algorithms to maximize his…

Computer Science and Game Theory · Computer Science 2022-02-22 Maurizio D 'Andrea

We introduce the application of online learning in a Stackelberg game pertaining to a system with two learning agents in a dyadic exchange network, consisting of a supplier and retailer, specifically where the parameters of the demand…

Computational Engineering, Finance, and Science · Computer Science 2024-10-15 Larkin Liu , Yuming Rong

We consider the problem of learning to exploit learning algorithms through repeated interactions in games. Specifically, we focus on the case of repeated two player, finite-action games, in which an optimizer aims to steer a no-regret…

Computer Science and Game Theory · Computer Science 2025-05-29 Yizhou Zhang , Yi-An Ma , Eric Mazumdar

We study the problem of online learning in a two-player decentralized cooperative Stackelberg game. In each round, the leader first takes an action, followed by the follower who takes their action after observing the leader's move. The goal…

Machine Learning · Computer Science 2023-04-13 Geng Zhao , Banghua Zhu , Jiantao Jiao , Michael I. Jordan

We initiate the study of structured Stackelberg games, a novel form of strategic interaction between a leader and a follower where contextual information can be predictive of the follower's (unknown) type. Motivated by applications such as…

Computer Science and Game Theory · Computer Science 2026-05-18 Maria-Florina Balcan , Kiriaki Fragkia , Keegan Harris

In a multi-follower Bayesian Stackelberg game, a leader plays a mixed strategy over $L$ actions to which $n\ge 1$ followers, each having one of $K$ possible private types, best respond. The leader's optimal strategy depends on the…

Computer Science and Game Theory · Computer Science 2026-03-03 Gerson Personnat , Tao Lin , Safwan Hossain , David C. Parkes

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 consider a repeated Stackelberg game setup where the leader faces a sequence of followers of unknown types and must learn what commitments to make. While previous works have considered followers that best respond to the commitment…

Computer Science and Game Theory · Computer Science 2024-12-10 Vijeth Hebbar , Cédric Langbort

Stackelberg equilibrium is a solution concept that describes optimal strategies to commit: Player 1 (the leader) first commits to a strategy that is publicly announced, then Player 2 (the follower) plays a best response to the leader's…

Computer Science and Game Theory · Computer Science 2021-11-04 Aditya Aradhye , Branislav Bošanský , Michael Hlaváček

Many real-world strategic games involve interactions between multiple players. We study a hierarchical multi-player game structure, where players with asymmetric roles can be separated into leaders and followers, a setting often referred to…

Machine Learning · Computer Science 2022-10-25 Yaolong Yu , Haifeng Xu , Haipeng Chen
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