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This paper studies a linear-quadratic mean-field game of stochastic large-population system, where the large-population system satisfies a class of $N$ weakly coupled linear backward stochastic differential equation. Different from the…

Optimization and Control · Mathematics 2024-12-02 Yu Si , Jingtao Shi

Recently, the paper [12] introduces a derivative-free consensus-based particle method that finds the Nash equilibrium of non-convex multiplayer games, where it proves the global exponential convergence in the sense of mean-field law. This…

Optimization and Control · Mathematics 2025-05-21 Hui Huang , Jethro Warnett

We address the generalized Nash equilibrium seeking problem in a partial-decision information scenario, where each agent can only exchange information with some neighbors, although its cost function possibly depends on the strategies of all…

Optimization and Control · Mathematics 2021-12-14 Mattia Bianchi , Giuseppe Belgioioso , Sergio Grammatico

We introduce a mean field model for optimal holding of a representative agent of her peers as a natural expected scaling limit from the corresponding $N-$agent model. The induced mean field dynamics appear naturally in a form which is not…

Optimization and Control · Mathematics 2022-04-05 Mao Fabrice Djete , Nizar Touzi

We consider a general nonzero-sum impulse game with two players. The main mathematical contribution of the paper is a verification theorem which provides, under some regularity conditions, a suitable system of quasi-variational inequalities…

Probability · Mathematics 2018-11-09 René Aïd , Matteo Basei , Giorgia Callegaro , Luciano Campi , Tiziano Vargiolu

Considering infinite-horizon, discrete-time, linear quadratic, N-player dynamic games with scalar dynamics, a graphical representation of feedback Nash equilibrium solutions is provided. This representation is utilised to derive conditions…

Optimization and Control · Mathematics 2025-01-27 Benita Nortmann , Mario Sassano , Thulasi Mylvaganam

In this paper, we consider a partial observed two-person zero-sum stochastic differential game problem where the system is governed by a stochastic differential equation of mean-field type. Under standard assumptions on the coefficients,…

Optimization and Control · Mathematics 2016-11-15 Maoning Tang , Qingxin Meng

In this paper we investigate Nash equilibrium payoffs for two-player nonzero-sum stochastic differential games whose cost functionals are defined by a system of coupled backward stochastic differential equations. We obtain an existence…

Probability · Mathematics 2014-01-21 Qian Lin

The purpose of this paper is to provide a complete probabilistic analysis of a large class of stochastic differential games for which the interaction between the players is of mean-field type. We implement the Mean-Field Games strategy…

Probability · Mathematics 2012-10-23 Rene Carmona , Francois Delarue

We show the convergence of finite state symmetric N-player differential games, where players control their transition rates from state to state, to a limiting dynamics given by a finite state Mean Field Game system made of two coupled…

Probability · Mathematics 2018-12-05 Alekos Cecchin , Guglielmo Pelino

In this paper, we are concerned with a stochastic optimal control problem of mean-field type under partial observation, where the state equation is governed by the controlled nonlinear mean-field stochastic differential equation, moreover…

Optimization and Control · Mathematics 2016-11-15 Maonin Tang , Qingxin Meng

This paper studies a two-player nonzero-sum stochastic differential game governed by a controlled convection-diffusion stochastic partial differential equation (SPDE) with spatially heterogeneous coefficients. The diffusion and transport…

Probability · Mathematics 2026-04-06 Nacira Agram , Eya Zougar

In this paper, we study the infinite-time mean field games with discounting, establishing an equilibrium where individual optimal strategies collectively regenerate the mean-field distribution. To solve this problem, we partition all agents…

Optimization and Control · Mathematics 2026-03-17 Yongsheng Song , Zeyu Yang

This paper studies a class of stationary mean-field games of singular stochastic control with regime-switching. The representative agent adjusts the dynamics of a Markov-modulated It\^o-diffusion via a two-sided singular stochastic control…

Optimization and Control · Mathematics 2024-12-31 Jodi Dianetti , Giorgio Ferrari , Ioannis Tzouanas

We investigate mean-field games (MFG) in which agents can actively control their speed of access to information. Specifically, the agents can dynamically decide to obtain observations with reduced delay by accepting higher observation…

Optimization and Control · Mathematics 2025-06-03 Dirk Becherer , Christoph Reisinger , Jonathan Tam

We consider the mean-field game where each agent determines the optimal time to exit the game by solving an optimal stopping problem with reward function depending on the density of the state processes of agents still present in the game.…

Optimization and Control · Mathematics 2020-07-09 Géraldine Bouveret , Roxana Dumitrescu , Peter Tankov

The large-population system consists of considerable small agents whose individual behavior and mass effect are interrelated via their state-average. The mean-field game provides an efficient way to get the decentralized strategies of…

Optimization and Control · Mathematics 2014-03-25 Jianhui Huang , Shujun Wang

We prove that differential Nash equilibria are generic amongst local Nash equilibria in continuous zero-sum games. That is, there exists an open-dense subset of zero-sum games for which local Nash equilibria are non-degenerate differential…

Computer Science and Game Theory · Computer Science 2020-02-05 Eric Mazumdar , Lillian Ratliff

In multi-agent autonomous systems, deception is a fundamental concept which characterizes the exploitation of unbalanced information to mislead victims into choosing oblivious actions. This effectively alters the system's long term…

Systems and Control · Electrical Eng. & Systems 2025-08-27 Michael Tang , Miroslav Krstic , Jorge Poveda

We derive the rate of convergence to the strongly variationally stable Nash equilibrium in a convex game, for a zeroth-order learning algorithm. Though we do not assume strong monotonicity of the game, our rates for the one-point feedback…

Optimization and Control · Mathematics 2024-03-12 Tatiana Tatarenko , Maryam Kamgarpour
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