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相关论文: A system level approach to generalised feedback Na…

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This work proposes a policy learning algorithm for seeking generalised feedback Nash equilibria (GFNE) in $N_P$-player noncooperative dynamic games. We consider linear-quadratic games with stochastic dynamics and design a best-response…

最优化与控制 · 数学 2025-06-13 Otacilio B. L. Neto , Michela Mulas , Francesco Corona

In this paper, we solve the problem of learning a generalized Nash equilibrium (GNE) in merely monotone games. First, we propose a novel continuous semi-decentralized solution algorithm without projections that uses first-order information…

系统与控制 · 电气工程与系统科学 2021-10-07 Suad Krilašević , Sergio Grammatico

In this paper, we consider the problem of learning a generalized Nash equilibrium (GNE) in strongly monotone games. First, we propose a novel continuous-time solution algorithm that uses regular projections and first-order information. As…

系统与控制 · 电气工程与系统科学 2020-07-23 Suad Krilašević , Sergio Grammatico

In this paper, a distributed non-model based seeking algorithm which combines the extremum seeking control (ESC) jointly with learning algorithms is proposed to seek a generalized Nash equilibrium (GNE) for a class of noncooperative games…

最优化与控制 · 数学 2023-02-27 Feng Xiao , Xin Cai , Bo Wei

Non-cooperative dynamic game theory provides a principled approach to modeling sequential decision-making among multiple noncommunicative agents. A key focus has been on finding Nash equilibria in two-agent zero-sum dynamic games under…

计算机科学与博弈论 · 计算机科学 2025-03-20 Kushagra Gupta , Ross Allen , David Fridovich-Keil , Ufuk Topcu

This paper presents algorithms for non-zero sum nonlinear constrained dynamic games with full information. Such problems emerge when multiple players with action constraints and differing objectives interact with the same dynamic system.…

系统与控制 · 电气工程与系统科学 2020-01-08 Bolei Di , Andrew Lamperski

We solve the stochastic generalized Nash equilibrium (SGNE) problem in merely monotone games with expected value cost functions. Specifically, we present the first distributed SGNE seeking algorithm for monotone games that requires one…

最优化与控制 · 数学 2021-07-15 Barbara Franci , Sergio Grammatico

We consider seeking generalized Nash equilibria (GNE) for noncooperative games with coupled nonlinear constraints over networks. We first revisit a well-known gradientplay dynamics from a passivity-based perspective, and address that the…

最优化与控制 · 数学 2024-08-23 Weijian Li , Lacra Pavel

In this work, we investigate the distributed generalized Nash equilibrium (GNE) seeking problems for $N$-coalition games with inequality constraints. First, we study the scenario where each agent in a coalition has full information of all…

最优化与控制 · 数学 2021-09-28 Chao Sun , Guoqiang Hu

A fundamental open problem in monotone game theory is the computation of a specific generalized Nash equilibrium (GNE) among all the available ones, e.g. the optimal equilibrium with respect to a system-level objective. The existing GNE…

系统与控制 · 电气工程与系统科学 2022-03-16 Emilio Benenati , Wicak Ananduta , Sergio Grammatico

We present the concept of a Generalized Feedback Nash Equilibrium (GFNE) in dynamic games, extending the Feedback Nash Equilibrium concept to games in which players are subject to state and input constraints. We formalize necessary and…

最优化与控制 · 数学 2023-11-22 Forrest Laine , David Fridovich-Keil , Chih-Yuan Chiu , Claire Tomlin

This paper proposes a general framework for constructing feedback controllers that drive complex dynamical systems to "efficient" steady-state (or slowly varying) operating points. Efficiency is encoded using generalized equations which can…

Decentralized online learning for seeking generalized Nash equilibrium (GNE) of noncooperative games in dynamic environments is studied in this paper. Each player aims at selfishly minimizing its own time-varying cost function subject to…

最优化与控制 · 数学 2021-05-14 Min Meng , Xiuxian Li , Yiguang Hong , Jie Chen , Long Wang

This paper introduces a new method to achieve stable convergence to Nash equilibrium in duopoly noncooperative games. Inspired by the recent fixed-time Nash Equilibrium seeking (NES) as well as prescribed-time extremum seeking (ES) and…

最优化与控制 · 数学 2024-05-27 Victor Hugo Pereira Rodrigues , Tiago Roux Oliveira , Miroslav Krstić , Tamer Başar

We address the generalized Nash equilibrium seeking problem for a population of agents playing aggregative games with affine coupling constraints. We focus on semi-decentralized communication architectures, where there is a central…

最优化与控制 · 数学 2022-06-16 Giuseppe Belgioioso , Sergio Grammatico

We consider a system of single- or double integrator agents playing a generalized Nash game over a network, in a partial-information scenario. We address the generalized Nash equilibrium seeking problem by designing a fully-distributed…

最优化与控制 · 数学 2021-05-07 Mattia Bianchi , Sergio Grammatico

In this paper, we focus on the stochastic generalized Nash equilibrium problem (SGNEP) which is an important and widely-used model in many different fields. In this model, subject to certain global resource constraints, a set of…

系统与控制 · 电气工程与系统科学 2022-02-01 Yuanhanqing Huang , Jianghai Hu

In this paper, we propose an asynchronous distributed algorithm for the computation of generalized Nash equilibria in noncooperative games, where the players interact via an undirected communication graph. Specifically, we extend the paper…

计算机科学与博弈论 · 计算机科学 2024-12-20 Carlo Cenedese , Giuseppe Belgioioso , Sergio Grammatico , Ming Cao

Generalized Nash equilibrium (GNE) is a solution concept for complete information games, in which each player's objective function and feasible region depend on other players' actions. While numerical methods for finding GNE when players…

最优化与控制 · 数学 2025-12-10 Stuart M. Harwood , Dimitri J. Papageorgiou

We consider seeking a Nash equilibrium (NE) of a monotone game, played by dynamic agents which are modeled as a class of lower-triangular nonlinear uncertain dynamics with external disturbances. We establish a general framework that…

最优化与控制 · 数学 2025-11-04 Weijian Li , Yutao Tang
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