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The Stackelberg game model, where a leader commits to a strategy and the follower best responds, has found widespread application, particularly to security problems. In the security setting, the goal is for the leader to compute an optimal…

Computer Science and Game Theory · Computer Science 2022-09-19 Sai Mali Ananthanarayanan , Christian Kroer

Automated decision-making tools increasingly assess individuals to determine if they qualify for high-stakes opportunities. A recent line of research investigates how strategic agents may respond to such scoring tools to receive favorable…

Machine Learning · Computer Science 2021-10-28 Keegan Harris , Hoda Heidari , Zhiwei Steven Wu

In multi-agent problems requiring a high degree of cooperation, success often depends on the ability of the agents to adapt to each other's behavior. A natural solution concept in such settings is the Stackelberg equilibrium, in which the…

Machine Learning · Computer Science 2024-06-14 Robert Loftin , Mustafa Mert Çelikok , Herke van Hoof , Samuel Kaski , Frans A. Oliehoek

Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may face the exact opposite of this game-theoretic problem --…

Computer Science and Game Theory · Computer Science 2022-10-05 Jibang Wu , Weiran Shen , Fei Fang , Haifeng Xu

Guided cooperation allows intelligent agents with heterogeneous capabilities to work together by following a leader-follower type of interaction. However, the associated control problem becomes challenging when the leader agent does not…

Systems and Control · Electrical Eng. & Systems 2024-02-01 Yuhan Zhao , Quanyan Zhu

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

The hierarchical interaction between the actor and critic in actor-critic based reinforcement learning algorithms naturally lends itself to a game-theoretic interpretation. We adopt this viewpoint and model the actor and critic interaction…

Machine Learning · Computer Science 2021-09-28 Liyuan Zheng , Tanner Fiez , Zane Alumbaugh , Benjamin Chasnov , Lillian J. Ratliff

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

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 study a two-player Stackelberg game with incomplete information such that the follower's strategy belongs to a known family of parameterized functions with an unknown parameter vector. We design an adaptive learning approach to…

Computer Science and Game Theory · Computer Science 2021-01-12 Guosong Yang , Radha Poovendran , João P. Hespanha

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

This paper investigates a robust incentive Stackelberg stochastic differential game problem for a linear-quadratic mean field system, where the model uncertainty appears in the drift term of the leader's state equation. Moreover, both the…

Optimization and Control · Mathematics 2026-03-31 Na Xiang , Jingtao Shi

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

In this paper, we introduce the third party to achieve the Stackelberg equilibrium with the time inconsistency in three different Stackelberg games, which are the discrete-time games, the dynamic games, and the mean field games. Here all…

Optimization and Control · Mathematics 2024-07-29 Yiming Jiang , Yawei Wei , Jie Xue

In security games, the solution concept commonly used is that of a Stackelberg equilibrium where the defender gets to commit to a mixed strategy. The motivation for this is that the attacker can repeatedly observe the defender's actions and…

Computer Science and Game Theory · Computer Science 2016-10-17 Vincent Conitzer

Dynamic Stackelberg games are a broad class of two-player games in which the leader acts first, and the follower chooses a response strategy to the leader's strategy. Unfortunately, only stylized Stackelberg games are explicitly solvable…

Optimization and Control · Mathematics 2024-11-15 Guillermo Alvarez , Ibrahim Ekren , Anastasis Kratsios , Xuwei Yang

Stackelberg games (SGs) constitute the most fundamental and acclaimed models of strategic interactions involving some form of commitment. Moreover, they form the basis of more elaborate models of this kind, such as, e.g., Bayesian…

Computer Science and Game Theory · Computer Science 2024-05-14 Francesco Bacchiocchi , Matteo Bollini , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Stackelberg games have been widely used to model interactive decision-making problems in a variety of domains such as energy systems, transportation, cybersecurity, and human-robot interaction. However, existing algorithms for solving…

Optimization and Control · Mathematics 2023-03-14 Yansong Li , Shuo Han

In this paper, we present an efficient algorithm to solve online Stackelberg games, featuring multiple followers, in a follower-agnostic manner. Unlike previous works, our approach works even when leader has no knowledge about the…

Optimization and Control · Mathematics 2024-03-28 Chinmay Maheshwari , James Cheng , S. Shankar Sasty , Lillian Ratliff , Eric Mazumdar

Commitments play a crucial role in game theory, shaping strategic interactions by either altering a player's own payoffs or influencing the incentives of others through outcome-contingent payments. While most research has focused on using…

Computer Science and Game Theory · Computer Science 2025-07-30 Maria Alejandra Ramirez , Rosemarie Nagel , David Wolpert , Jürgen Jost