中文
相关论文

相关论文: A method for multi-leader-multi-follower games by …

200 篇论文

The paper is devoted to inverse Stackelberg games with many players. We consider both static and differential games. The main assumption of the paper is the compactness of the strategy sets. We obtain the characterization of inverse…

最优化与控制 · 数学 2014-04-21 Yurii Averboukh

We analyze linear McKean-Vlasov forward-backward SDEs arising in leader-follower games with mean-field type control and terminal state constraints on the state process. We establish an existence and uniqueness of solutions result for such…

数理金融 · 定量金融 2018-09-13 Guanxing Fu , Ulrich Horst

Stackelberg equilibrium is a solution concept in two-player games where the leader has commitment rights over the follower. In recent years, it has become a cornerstone of many security applications, including airport patrolling and…

计算机科学与博弈论 · 计算机科学 2021-02-04 Chun Kai Ling , Noam Brown

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…

最优化与控制 · 数学 2026-04-30 Silvia Cianchi , Anibal Sanjab , Sergio Grammatico

This contribution deals with a two-level discrete decision problem, a so-called Stackelberg strategic game: A Subset Sum setting is addressed with a set $N$ of items with given integer weights. One distinguished player, the leader, may…

离散数学 · 计算机科学 2018-01-12 Ulrich Pferschy , Gaia Nicosia , Andrea Pacifici

Non-cooperative and cooperative games with a very large number of players have many applications but remain generally intractable when the number of players increases. Introduced by Lasry and Lions, and Huang, Caines and Malham\'e, Mean…

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…

最优化与控制 · 数学 2022-10-11 Xin Guo , Anran Hu , Jiacheng Zhang

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…

机器学习 · 计算机科学 2025-05-06 Yaolong Yu , Haipeng Chen

In this paper, we study large population multi-agent reinforcement learning (RL) in the context of discrete-time linear-quadratic mean-field games (LQ-MFGs). Our setting differs from most existing work on RL for MFGs, in that we consider a…

系统与控制 · 电气工程与系统科学 2020-10-02 Muhammad Aneeq uz Zaman , Kaiqing Zhang , Erik Miehling , Tamer Başar

This paper is concerned with a three-level multi-leader-follower incentive Stackelberg game with $H_\infty$ constraint. Based on $H_2/H_\infty$ control theory, we firstly obtain the worst-case disturbance and the team-optimal strategy by…

最优化与控制 · 数学 2024-12-13 Na Xiang , Jingtao Shi

In this paper we formulate and analyze an $N$-player stochastic game of the classical fuel follower problem and its Mean Field Game (MFG) counterpart. For the $N$-player game, we obtain the Nash Equilibrium (NE) explicitly by deriving and…

最优化与控制 · 数学 2019-04-30 Xin Guo , Renyuan Xu

Mean field games (MFG) and mean field control (MFC) are critical classes of multi-agent models for efficient analysis of massive populations of interacting agents. Their areas of application span topics in economics, finance, game theory,…

机器学习 · 计算机科学 2022-06-08 Lars Ruthotto , Stanley Osher , Wuchen Li , Levon Nurbekyan , Samy Wu Fung

This paper investigates a linear quadratic mean field leader-follower team problem, where the model involves one leader and a large number of weakly-coupled interactive followers. The leader and the followers cooperate to optimize the…

最优化与控制 · 数学 2020-08-13 Jianhui Huang , Bing-Chang Wang , Tinghan Xie

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…

最优化与控制 · 数学 2024-11-15 Guillermo Alvarez , Ibrahim Ekren , Anastasis Kratsios , Xuwei Yang

In this paper, the known deterministic linear-quadratic Stackelberg game is revisited, whose open-loop Stackelberg solution actually possesses the nature of time inconsistency. To handle this time inconsistency, {a two-tier game framework…

最优化与控制 · 数学 2022-03-09 Yuan-Hua Ni , Liping Liu , Xinzhen Zhang

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…

最优化与控制 · 数学 2024-12-30 Zhun Gou , Nan-Jing Huang , Xian-Jun Long , Jian-Hao Kang

Effectively predicting intent and behavior requires inferring leadership in multi-agent interactions. Dynamic games provide an expressive theoretical framework for modeling these interactions. Employing this framework, we propose a novel…

多智能体系统 · 计算机科学 2024-04-10 Hamzah Khan , David Fridovich-Keil

We study the problem of computing Stackelberg equilibria Stackelberg games whose underlying structure is in congestion games, focusing on the case where each player can choose a single resource (a.k.a. singleton congestion games) and one of…

计算机科学与博弈论 · 计算机科学 2018-08-31 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti , Stefano Coniglio

We study the control of rumor propagation in large networked populations by using Stackelberg graphon games. We first introduce a principal who wants to incentivize the spread of her preferred news and discourage the spread of non-preferred…

最优化与控制 · 数学 2026-04-29 Huaning Liu , Gokce Dayanikli

Stackelberg security game models and associated computational tools have seen deployment in a number of high-consequence security settings, such as LAX canine patrols and Federal Air Marshal Service. These models focus on isolated systems…

计算机科学与博弈论 · 计算机科学 2015-05-29 Jian Lou , Andrew M. Smith , Yevgeniy Vorobeychik