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Inverse game theory is utilized to infer the cost functions of all players based on game outcomes. However, existing inverse game theory methods do not consider the learner as an active participant in the game, which could significantly…

Computer Science and Game Theory · Computer Science 2025-10-20 Jianguo Chen , Jinlong Lei , Biqiang Mu , Yiguang Hong , Hongsheng Qi

In this paper, we introduce the third party to achieve the Stackelberg equilibrium with the time inconsistency in three different Stackelberg games, which are the discrete-time games, the dynamic games, and the mean field games. Here all…

Optimization and Control · Mathematics 2024-07-29 Yiming Jiang , Yawei Wei , Jie Xue

We study payoff manipulation in repeated multi-objective Stackelberg games, where a leader may strategically influence a follower's deterministic best response, e.g., by offering a share of their own payoff. We assume that the follower's…

Computer Science and Game Theory · Computer Science 2025-08-27 Phurinut Srisawad , Juergen Branke , Long Tran-Thanh

We consider the charge scheduling coordination of a fleet of plug-in electric vehicles, developing a hybrid decision-making framework for efficient and profitable usage of the distribution grid. Each charging dynamics, affected by the…

Optimization and Control · Mathematics 2019-10-24 Carlo Cenedese , Filippo Fabiani , Michele Cucuzzella , Jacquelien M. A. Scherpen , Ming Cao , Sergio Grammatico

The notion of approachability was introduced by Blackwell [1] in the context of vector-valued repeated games. The famous Blackwell's approachability theorem prescribes a strategy for approachability, i.e., for `steering' the average cost of…

Machine Learning · Computer Science 2016-06-22 Dileep Kalathil , Vivek Borkar , Rahul Jain

Nash equilibrium is a central concept in game theory. Several Nash solvers exist, yet none scale to normal-form games with many actions and many players, especially those with payoff tensors too big to be stored in memory. In this work, we…

Computer Science and Game Theory · Computer Science 2022-02-07 Ian Gemp , Rahul Savani , Marc Lanctot , Yoram Bachrach , Thomas Anthony , Richard Everett , Andrea Tacchetti , Tom Eccles , János Kramár

Decoding how rational agents should behave in shared systems remains a critical challenge within theoretical computer science, artificial intelligence and economics studies. Central to this challenge is the task of computing the solution…

Computer Science and Game Theory · Computer Science 2025-01-07 Dongge Wang , Xiang Yan , Zehao Dou , Wenhan Huang , Yaodong Yang , Xiaotie Deng

Remote estimation is a crucial element of real time monitoring of a stochastic process. While most of the existing works have concentrated on obtaining optimal sampling strategies, motivated by malicious attacks on cyber-physical systems,…

Information Theory · Computer Science 2024-12-03 Atahan Dokme , Raj Kiriti Velicheti , Melih Bastopcu , Tamer Başar

We study a two-player Stackelberg game with incomplete information such that the follower's strategy belongs to a known family of parameterized functions with an unknown parameter vector. We design an adaptive learning approach to…

Computer Science and Game Theory · Computer Science 2021-01-12 Guosong Yang , Radha Poovendran , João P. Hespanha

In modern buildings renewable energy generators and storage devices are spreading, and consequently the role of the users in the power grid is shifting from passive to active. We design a demand response scheme that exploits the prosumers'…

Systems and Control · Electrical Eng. & Systems 2022-11-10 Marta Fochesato , Carlo Cenedese , John Lygeros

We study policy optimization algorithms for computing correlated equilibria in multi-player general-sum Markov Games. Previous results achieve $O(T^{-1/2})$ convergence rate to a correlated equilibrium and an accelerated $O(T^{-3/4})$…

Machine Learning · Computer Science 2024-05-03 Yang Cai , Haipeng Luo , Chen-Yu Wei , Weiqiang Zheng

This paper is concerned with the stochastic linear quadratic Stackelberg differential game with overlapping information, where the diffusion terms contain the control and state variables. Here the term "overlapping" means that there are…

Optimization and Control · Mathematics 2018-05-01 Jingtao Shi , Guangchen Wang , Jie Xiong

This paper is concerned with a linear-quadratic partially observed Stackelberg stochastic differential game with correlated state and observation noises, where the diffusion coefficient does not contain the control variable and the control…

Optimization and Control · Mathematics 2021-05-25 Yueyang Zheng , Jingtao Shi

This paper addresses a linear-quadratic Stackelberg mean field (MF) games and teams problem with arbitrary population sizes, where the game among the followers is further categorized into two types: non-cooperative and cooperative, and the…

Optimization and Control · Mathematics 2024-12-24 Wenyu Cong , Jingtao Shi , Bingchang Wang

We design a computational approach to find equilibria in a class of Nash games possessing a hierarchical structure. By using tools from mixed-integer optimization and the characterization of variational equilibria in terms of the…

Optimization and Control · Mathematics 2024-11-12 Barbara Franci , Filippo Fabiani , Martin Schmidt , Mathias Staudigl

We present polynomial-time algorithms as well as hardness results for equilibrium computation in atomic splittable routing games, for the case of general convex cost functions. These games model traffic in freight transportation, market…

Computer Science and Game Theory · Computer Science 2018-04-27 Umang Bhaskar , Phani Raj Lolakapuri

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…

Optimization and Control · Mathematics 2020-03-31 Yipeng Pang , Guoqiang Hu

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…

Machine Learning · Computer Science 2025-05-06 Yaolong Yu , Haipeng Chen

We consider a number of questions related to tradeoffs between reward and regret in repeated gameplay between two agents. To facilitate this, we introduce a notion of $\textit{generalized equilibrium}$ which allows for asymmetric regret…

Computer Science and Game Theory · Computer Science 2023-12-19 William Brown , Jon Schneider , Kiran Vodrahalli

The multi-cluster games are addressed in this paper, where all players team up with the players in the cluster that they belong to, and compete against the players in other clusters to minimize the cost function of their own cluster. The…

Systems and Control · Electrical Eng. & Systems 2023-06-19 Zhenhua Deng , Yan Zhao