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We study incentive designs for a class of stochastic Stackelberg games with one leader and a large number of (finite as well as infinite population of) followers. We investigate whether the leader can craft a strategy under a dynamic…

Computer Science and Game Theory · Computer Science 2024-02-13 Sina Sanjari , Subhonmesh Bose , Tamer Başar

The multilevel reverse Stackelberg game is considered. In this game, the leader controls the outcome by announcing a strategy as a function of decision variables of the followers to his/her own decision space. Corresponding to the leader's…

Optimization and Control · Mathematics 2023-03-01 Seyfe Belete Worku , Birilew Belayneh Tsegaw , Semu Mitiku Kassa

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

Stackelberg games are a classic example of bilevel optimization problems, which are often encountered in game theory and economics. These are complex problems with a hierarchical structure, where one optimization task is nested within the…

Computer Science and Game Theory · Computer Science 2013-07-25 Ankur Sinha , Pekka Malo , Anton Frantsev , Kalyanmoy Deb

Stackelberg games originate where there are market leaders and followers, and the actions of leaders influence the behavior of the followers. Mathematical modelling of such games results in what's called a Bilevel Optimization problem.…

Computer Science and Game Theory · Computer Science 2023-12-07 Pravesh Koirala , Forrest Laine

Existing methods for learning Stackelberg equilibria typically assume that the followers' (variational, generalized) Nash equilibrium is unique. However, in the presence of multiple equilibria, without a selection convention, the problem…

Optimization and Control · Mathematics 2026-04-30 Silvia Cianchi , Anibal Sanjab , Sergio Grammatico

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

We provide a general approach to reformulating any continuous-time stochastic Stackelberg differential game under closed-loop strategies as a single-level optimisation problem with target constraints. More precisely, we consider a…

Optimization and Control · Mathematics 2026-05-14 Camilo Hernández , Nicolás Hernández Santibáñez , Emma Hubert , Dylan Possamaï

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 introduce and study incentive equilibria for multi-player meanpayoff games. Incentive equilibria generalise well-studied solution concepts such as Nash equilibria and leader equilibria (also known as Stackelberg equilibria). Recall that…

Computer Science and Game Theory · Computer Science 2015-11-03 Anshul Gupta , M. S. Krishna Deepak , Bharath Kumar Padarthi , Sven Schewe , Ashutosh Trivedi

This paper proposes and studies a class of discrete-time finite-time-horizon Stackelberg mean-field games, with one leader and an infinite number of identical and indistinguishable followers. In this game, the objective of the leader is to…

Optimization and Control · Mathematics 2022-10-11 Xin Guo , Anran Hu , Jiacheng Zhang

A growing body of work in game theory extends the traditional Stackelberg game to settings with one leader and multiple followers who play a Nash equilibrium. Standard approaches for computing equilibria in these games reformulate the…

Computer Science and Game Theory · Computer Science 2021-12-07 Kai Wang , Lily Xu , Andrew Perrault , Michael K. Reiter , Milind Tambe

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

This paper is concerned with a two-person zero-sum indefinite stochastic linear-quadratic Stackelberg differential game with asymmetric informational uncertainties, where both the leader and follower face different and unknown disturbances.…

Optimization and Control · Mathematics 2024-07-09 Na Xiang , Jingtao Shi

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 this paper, we are concerned with the stabilizatbility of Stackelberg game-based systems. In particular, two players are involved in the system where one is the follower to minimize the related cost function and the other is the leader…

Optimization and Control · Mathematics 2021-05-04 Yue Sun , Juanjuan Xu , Huanshui Zhang

The Stackelberg game depicts a leader-follower relationship wherein decisions are made sequentially, and the Stackelberg equilibrium represents an expected optimal solution when the leader can anticipate the rational response of the…

Systems and Control · Electrical Eng. & Systems 2024-01-17 Yue Chen , Peng Yi

Strategic interaction in congested systems is commonly modelled using Stackelberg games, where competing leaders anticipate the behaviour of self-interested followers. A key limitation of existing models is that they typically ignore agents…

Multiagent Systems · Computer Science 2026-03-06 Niloofar Aminikalibar , Farzaneh Farhadi , Maria Chli

This paper investigates the non-zero-sum linear-quadratic stochastic Stackelberg differential games with affine constraints, which depend on both the follower's response and the leader's strategy. With the help of the stochastic Riccati…

Optimization and Control · Mathematics 2024-12-30 Zhun Gou , Nan-Jing Huang , Xian-Jun Long , Jian-Hao Kang

This paper obtains the maximum principle for both stochastic (global) open-loop and stochastic (global) closed-loop Stackelberg differential games. For the closed-loop case, we use the theory of controlled forward-backward stochastic…

Optimization and Control · Mathematics 2012-10-30 Alain Bensoussan , Shaokuan Chen , Suresh P. Sethi
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