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This paper considers the distributed strategy design for Nash equilibrium (NE) seeking in multi-cluster games under a partial-decision information scenario. In the considered game, there are multiple clusters and each cluster consists of a…

最优化与控制 · 数学 2022-06-08 Min Meng , Xiuxian Li

The distributed computation of Nash equilibria is assuming growing relevance in engineering where such problems emerge in the context of distributed control. Accordingly, we present schemes for computing equilibria of two classes of static…

最优化与控制 · 数学 2017-10-17 Hao Jiang , Uday V. Shanbhag , Sean P. Meyn

Coordinating the behaviour of self-interested agents in the presence of multiple Nash equilibria is a major research challenge for multi-agent systems. Pre-game communication between all the players can aid coordination in cases where the…

计算机科学与博弈论 · 计算机科学 2025-02-18 Wei-Chen Lee , Alessandro Abate , Michael Wooldridge

Learning in games provides a powerful framework to design control policies for self-interested agents that may be coupled through their dynamics, costs, or constraints. We consider the case where the dynamics of the coupled system can be…

系统与控制 · 电气工程与系统科学 2024-09-18 Mostafa M. Shibl , Vijay Gupta

We consider a subclass of $n$-player stochastic games, in which players have their own internal state/action spaces while they are coupled through their payoff functions. It is assumed that players' internal chains are driven by independent…

机器学习 · 计算机科学 2023-03-23 S. Rasoul Etesami

Partially Observable Markov Games (POMGs) provide a general framework for modeling multi-agent sequential decision-making under asymmetric information. A common approach is to reformulate a POMG as a fully observable Markov game over belief…

多智能体系统 · 计算机科学 2026-04-08 Lan Sang , Chinmay Maheshwari

We consider two-player contests with the possibility of ties and study the effect of different tie-breaking rules on effort. For ratio-form and difference-form contests that admit pure-strategy Nash equilibrium, we find that the effort of…

理论经济学 · 经济学 2024-02-05 Sumit Goel , Amit Goyal

In this work, we provide a structural characterization of the possible Nash equilibria in the well-studied class of security games with additive utility. Our analysis yields a classification of possible equilibria into seven types and we…

计算机科学与博弈论 · 计算机科学 2022-08-05 Joe Clanin , Sourabh Bhattacharya

We consider a nonzero-sum N-player Markov game on an abstract measurable state space with compact metric action spaces. The payoff functions are bounded Carath\'eodory functions and the transitions of the system are assumed to have a…

最优化与控制 · 数学 2023-05-09 François Dufour , Tomás Prieto-Rumeau

This work proposes a novel distributed approach for computing a Nash equilibrium in convex games with merely monotone and restricted strongly monotone pseudo-gradients. By leveraging the idea of the centralized operator extrapolation method…

最优化与控制 · 数学 2025-07-18 Tatiana Tatarenko , Angelia Nedich

We propose a stochastic first-order algorithm to learn the rationality parameters of simultaneous and non-cooperative potential games, i.e., the parameters of the agents' optimization problems. Our technique combines (i.) an active-set step…

最优化与控制 · 数学 2023-07-31 Stefan Clarke , Gabriele Dragotto , Jaime Fernández Fisac , Bartolomeo Stellato

This paper considers a distributed Nash equilibrium seeking problem, where the players only have partial access to other players' actions, such as their neighbors' actions. Thus, the players are supposed to communicate with each other to…

最优化与控制 · 数学 2020-03-31 Yipeng Pang , Guoqiang Hu

We propose an adaptive incentive mechanism that learns the optimal incentives in environments where players continuously update their strategies. Our mechanism updates incentives based on each player's externality, defined as the difference…

计算机科学与博弈论 · 计算机科学 2025-03-04 Chinmay Maheshwari , Kshitij Kulkarni , Manxi Wu , Shankar Sastry

In this paper, we study which data can be induced by a correlated equilibrium given a known finite simultaneous move game. We assume that an analyst has access to the frequency of each agent's actions but does not have access to the…

理论经济学 · 经济学 2026-03-03 Christopher P. Chambers , Maxime Cugnon de Sévricourt , Christopher Turansick

Announcement games, where information is disseminated by announcers and challenged by validators, are prevalent in real-world scenarios. Validators take effort to verify the validity of the announcements, gaining rewards for successfully…

计算机科学与博弈论 · 计算机科学 2024-08-01 Siyuan Liu , Yulong Zeng

We consider the problem of learning Nash equilibrial policies for two-player risk-sensitive collision-avoiding interactions. Solving the Hamilton-Jacobi-Isaacs equations of such general-sum differential games in real time is an open…

机器人学 · 计算机科学 2025-03-21 Lei Zhang , Siddharth Das , Tanner Merry , Wenlong Zhang , Yi Ren

Synthesis of finite-state controllers from high-level specifications in multi-agent systems can be reduced to solving multi-player concurrent games over finite graphs. The complexity of solving such games with qualitative objectives for…

计算机科学与博弈论 · 计算机科学 2018-09-28 Shaull Almagor , Rajeev Alur , Suguman Bansal

Power system operators and electric utility companies often impose a coincident peak demand charge on customers when the aggregate system demand reaches its maximum. This charge incentivizes customers to strategically shift their peak usage…

系统与控制 · 电气工程与系统科学 2025-05-16 Liudong Chen , Jay Sethuraman , Bolun Xu

We design the first fully-distributed algorithm for generalized Nash equilibrium seeking in aggregative games on a time-varying communication network, under partial-decision information, i.e., the agents have no direct access to the…

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

We consider multi-agent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we…

最优化与控制 · 数学 2018-10-16 Tatiana Tatarenko , Maryam Kamgarpour