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In this paper, we present a novel consensus-based zeroth-order algorithm tailored for non-convex multiplayer games. The proposed method leverages a metaheuristic approach using concepts from swarm intelligence to reliably identify global…

Dynamical Systems · Mathematics 2024-07-30 Enis Chenchene , Hui Huang , Jinniao Qiu

The $1-N$ generalized Stackelberg game (single-leader multi-follower game) is intricately intertwined with the interaction between a leader and followers (hierarchical interaction) and the interaction among followers (simultaneous…

Computer Science and Game Theory · Computer Science 2023-06-12 Jaeyeon Jo , Jihwan Yu , Jinkyoo Park

Dynamic games provide a fundamental framework for multi-agent decision-making over time, yet computing feedback Nash equilibria (FNEs) in infinite-horizon discrete-time linear-quadratic (LQ) settings remains computationally challenging.…

Systems and Control · Electrical Eng. & Systems 2026-03-11 Shengyuan Huang , Xiaoguang Yang , Yifen Mu , Wenjun Mei

This paper is concerned with a linear-quadratic (LQ) leader-follower differential game with mixed deterministic and stochastic controls. In the game, the follower is a random controller which means that the follower can choose adapted…

Optimization and Control · Mathematics 2025-09-26 Jingtao Shi , Guangchen Wang

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

In zero-sum games, the optimal strategy is well-defined by the Nash equilibrium. However, it is overly conservative when playing against suboptimal opponents and it can not exploit their weaknesses. Limited look-ahead game solving in…

Computer Science and Game Theory · Computer Science 2024-04-04 David Milec , Ondřej Kubíček , Viliam Lisý

This paper studies policy optimization algorithms for multi-agent reinforcement learning. We begin by proposing an algorithm framework for two-player zero-sum Markov Games in the full-information setting, where each iteration consists of a…

Machine Learning · Computer Science 2022-07-26 Runyu Zhang , Qinghua Liu , Huan Wang , Caiming Xiong , Na Li , Yu Bai

While the topic of mean-field games (MFGs) has a relatively long history, heretofore there has been limited work concerning algorithms for the computation of equilibrium control policies. In this paper, we develop a computable policy…

Systems and Control · Electrical Eng. & Systems 2020-04-07 Muhammad Aneeq uz Zaman , Kaiqing Zhang , Erik Miehling , Tamer Başar

This paper presents a new primal-dual method for computing an equilibrium of generalized (continuous) Nash game (referred to as generalized Nash equilibrium problem (GNEP)) where each player's feasible strategy set depends on the other…

Computer Science and Game Theory · Computer Science 2022-03-04 Jong Gwang Kim

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 introduce a generalization of zero-sum network multiagent matrix games and prove that alternating gradient descent converges to the set of Nash equilibria at rate $O(1/T)$ for this set of games. Alternating gradient descent obtains this…

Computer Science and Game Theory · Computer Science 2021-10-07 James P. Bailey

In this paper we propose a numerical method to obtain an approximation of Nash equilibria for multi-player non-cooperative games with a special structure. We consider the infinite horizon problem in a case which leads to a system of…

Numerical Analysis · Mathematics 2016-02-19 Simone Cacace , Emiliano Cristiani , Maurizio Falcone

This work focuses on the entropy-regularized independent natural policy gradient (NPG) algorithm in multi-agent reinforcement learning. In this work, agents are assumed to have access to an oracle with exact policy evaluation and seek to…

Machine Learning · Computer Science 2024-05-07 Youbang Sun , Tao Liu , P. R. Kumar , Shahin Shahrampour

Recent extensions to dynamic games of the well-known fictitious play learning procedure in static games were proved to globally converge to stationary Nash equilibria in two important classes of dynamic games (zero-sum and…

Computer Science and Game Theory · Computer Science 2022-07-08 Lucas Baudin , Rida Laraki

We study the problem of computing an approximate Nash equilibrium of a game whose strategy space is continuous without access to gradients of the utility function. Such games arise, for example, when players' strategies are represented by…

Computer Science and Game Theory · Computer Science 2025-10-28 Carlos Martin , Tuomas Sandholm

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

We study a subclass of $n$-player stochastic games, namely, stochastic games with independent chains and unknown transition matrices. In this class of games, players control their own internal Markov chains whose transitions do not depend…

Computer Science and Game Theory · Computer Science 2023-12-05 Tiancheng Qin , S. Rasoul Etesami

This paper considers a class of noncooperative games in which the feasible decision sets of all players are coupled together by a coupled inequality constraint. Adopting the variational inequality formulation of the game, we first introduce…

Computer Science and Game Theory · Computer Science 2024-02-13 Huaqing Li , Liang Ran , Lifeng Zheng , Zhe Li , Jinhui Hu , Jun Li , Tingwen Huang

Resource competition problems are often modeled using Colonel Blotto games, where players take simultaneous actions. However, many real-world scenarios involve sequential decision-making rather than simultaneous moves. To model these…

Computer Science and Game Theory · Computer Science 2025-05-13 Yan Liu , Bonan Ni , Weiran Shen , Zihe Wang , Jie Zhang

We consider a dynamical approach to game in extensive forms. By restricting the convertibility relation over strategy profiles, we obtain a semi-potential (in the sense of Kukushkin), and we show that in finite games the corresponding…

Computer Science and Game Theory · Computer Science 2017-04-05 Stéphane Le Roux , Arno Pauly