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Decentralized learning has shown great promise for cooperative multi-agent reinforcement learning (MARL). However, non-stationarity remains a significant challenge in fully decentralized learning. In the paper, we tackle the…

Machine Learning · Computer Science 2023-02-08 Kefan Su , Siyuan Zhou , Jiechuan Jiang , Chuang Gan , Xiangjun Wang , Zongqing Lu

Coordinating communication and control is a key component in the stability and performance of networked multi-agent systems. While single user networked control systems have gained a lot of attention within this domain, in this work, we…

Optimization and Control · Mathematics 2025-06-25 Shubham Aggarwal , Muhammad Aneeq uz Zaman , Melih Bastopcu , Tamer Başar

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…

Robotics · Computer Science 2025-03-21 Lei Zhang , Siddharth Das , Tanner Merry , Wenlong Zhang , Yi Ren

We consider strongly monotone games with convex separable coupling constraints, played by dynamical agents, in a partial-decision information scenario. We start by designing continuous-time fully distributed feedback controllers, based on…

Optimization and Control · Mathematics 2021-05-05 Mattia Bianchi , Sergio Grammatico

Safety is critical during human-robot interaction. But -- because people are inherently unpredictable -- it is often difficult for robots to plan safe behaviors. Instead of relying on our ability to anticipate humans, here we identify robot…

Robotics · Computer Science 2026-04-07 Benjamin A. Christie , Dylan P. Losey

We investigate the linear quadratic Gaussian Stackelberg game under a class of nested observation information pattern. Two decision makers implement control strategies relying on different information sets: The follower uses its observation…

Optimization and Control · Mathematics 2022-06-07 Zhipeng Li , Damian Marelli , Minyue Fu , Huanshui Zhang

A distributed Nash equilibrium seeking algorithm is presented for networked games. We assume an incomplete information available to each player about the other players' actions. The players communicate over a strongly connected digraph to…

Systems and Control · Computer Science 2019-12-10 Farzad Salehisadaghiani , Lacra Pavel

Static reduction of information structures (ISs) is a method that is commonly adopted in stochastic control, team theory, and game theory. One approach entails change of measure arguments, which has been crucial for stochastic analysis and…

Optimization and Control · Mathematics 2023-07-13 Sina Sanjari , Tamer Başar , Serdar Yüksel

We consider a class of linear-quadratic-Gaussian mean-field games with a major agent and considerable heterogeneous minor agents in the presence of mean-field interactions. The individual admissible controls are constrained in closed convex…

Optimization and Control · Mathematics 2017-10-10 Ying Hu , Jianhui Huang , Tianyang Nie

Many resources are provided by an ecological system that is vulnerable to tipping when exceeding a certain level of pollution, with a sudden big loss of ecosystem services. An ecological system is usually also a common-pool resource and…

General Economics · Economics 2026-03-23 Yongyang Cai , Anastasios Xepapadeas , Aart de Zeeuw

We study a nonzero-sum stochastic differential game with both players adopting impulse controls, on a finite time horizon. The objective of each player is to maximize her total expected discounted profits. The resolution methodology relies…

Optimization and Control · Mathematics 2021-12-21 René Aïd , Lamia Ben Ajmia , M'hamed Gaïgi , Mohamed Mnif

In this paper, we propose a novel equilibrium solution notion for the time-inconsistent stochastic linear-quadratic optimal control problem. This notion is called the mixed equilibrium solution, which consists of two parts: a…

Optimization and Control · Mathematics 2018-08-21 Yuan-Hua Ni , Xun Li , Ji-Feng Zhang , Miroslav Krstic

In this work, we propose, for the first time, a reinforcement learning framework specifically designed for zero-sum linear-quadratic stochastic differential games. This approach offers a generalized solution for scenarios in which accurate…

Optimization and Control · Mathematics 2026-02-10 Yiyuan Wang

We propose a game-theoretic framework for adaptive multi-agent intelligent systems. Unlike classical game theory, which often treats strategies as primitive objects chosen by perfectly rational agents, the proposed framework provides a…

Neural and Evolutionary Computing · Computer Science 2026-05-12 Zhe Sage Chen , Quanyan Zhu

We consider two classes of constrained finite state-action stochastic games. First, we consider a two player nonzero sum single controller constrained stochastic game with both average and discounted cost criterion. We consider the same…

Optimization and Control · Mathematics 2012-06-11 Vikas Vikram Singh , N. Hemachandra

This paper considers linear quadratic team decision problems where the players in the team affect each other's information structure through their decisions. Whereas the stochastic version of the problem is well known to be complex with…

Optimization and Control · Mathematics 2013-02-05 Ather Gattami

In an inverse game problem, one needs to infer the cost function of the players in a game such that a desired joint strategy is a Nash equilibrium. We study the inverse game problem for a class of multiplayer matrix games, where the cost…

Computer Science and Game Theory · Computer Science 2022-10-17 Yue Yu , Jonathan Salfity , David Fridovich-Keil , Ufuk Topcu

This paper focuses on linear-quadratic (LQ for short) mean-field games described by forward-backward stochastic differential equations (FBSDEs for short), in which the individual control region is postulated to be convex. The decentralized…

Optimization and Control · Mathematics 2021-04-09 Liangquan Zhang , Xun Li

In this paper, we study a class of linear-quadratic (LQ) mean field games of controls with common noises and their corresponding $N$-player games. The theory of mean field game of controls considers a class of mean field games where the…

Optimization and Control · Mathematics 2022-06-13 Min Li , Chenchen Mou , Zhen Wu , Chao Zhou

In this paper, we study the problem of multiple stochastic agents interacting in a dynamic game scenario with continuous state and action spaces. We define a new notion of stochastic Nash equilibrium for boundedly rational agents, which we…

Optimization and Control · Mathematics 2021-10-05 Negar Mehr , Mingyu Wang , Mac Schwager