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This paper proposes and analyzes an iterative minimization formulation for search- ing index-1 saddle points of an energy function. This formulation differs from other eigenvector-following methods by constructing a new objective function…

Numerical Analysis · Mathematics 2014-06-10 Weiguo Gao , Jing Leng , Xiang Zhou

Human driver participation is a critical source of uncertainty in Mobility-on-Demand (MoD) rebalancing. Drivers follow platform recommendations probabilistically, and their willingness to comply evolves with experienced outcomes. This…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Avalpreet Singh Brar , Rong Su , Jaskaranveer Kaur , Gioele Zardini

We study a leader-follower system of interacting particles subject to feedback control and derive its mean-field limits through a two-step passage: first to a micro-macro system coupling leader particles with a follower fluid, and then to a…

Analysis of PDEs · Mathematics 2025-08-07 Giacomo Albi , Young-Pil Choi , Matteo Piu , Sihyun Song

Recent focus on robustness to adversarial attacks for deep neural networks produced a large variety of algorithms for training robust models. Most of the effective algorithms involve solving the min-max optimization problem for training…

Machine Learning · Computer Science 2021-03-03 Yasaman Esfandiari , Aditya Balu , Keivan Ebrahimi , Umesh Vaidya , Nicola Elia , Soumik Sarkar

In the stabilizing consensus problem, each agent of a networked system has an input value and is repeatedly writing an output value; it is required that eventually all the output values stabilize to the same value which, moreover, must be…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-24 Bernadette Charron-Bost , Shlomo Moran

The paper considers the problem of a leader that seeks to optimally influence the opinions of agents in a directed network through connecting with a limited number of the agents ("direct followers"), possibly in the presence of a fixed…

Optimization and Control · Mathematics 2018-06-20 Van Sy Mai , Eyad H. Abed

Mean-Field Control (MFC) is a powerful tool to solve Multi-Agent Reinforcement Learning (MARL) problems. Recent studies have shown that MFC can well-approximate MARL when the population size is large and the agents are exchangeable.…

Machine Learning · Computer Science 2022-06-02 Washim Uddin Mondal , Vaneet Aggarwal , Satish V. Ukkusuri

The problem of communicating sensor measurements over shared networks is prevalent in many modern large-scale distributed systems such as cyber-physical systems, wireless sensor networks, and the internet of things. Due to bandwidth…

Systems and Control · Electrical Eng. & Systems 2021-12-14 Marcos M. Vasconcelos

The small-world network model is a simple model of the structure of social networks, which simultaneously possesses characteristics of both regular lattices and random graphs. The model consists of a one-dimensional lattice with a low…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , C. Moore , D. J. Watts

In leader-follower multi-agent networks with switching topologies, choosing a subset of agents as leaders is a critical step to achieve desired performances. In this paper, we concentrate on the problem of selecting a minimum-size set of…

Multiagent Systems · Computer Science 2019-12-13 Kaile Chen , Wangli He , Yang Tang , Wenle Zhang

This paper is devoted to a Stackelberg stochastic differential game for a linear mean-field type stochastic differential system with a mean-field type quadratic cost functional in finite horizon. The coefficients in the state equation and…

Optimization and Control · Mathematics 2023-08-22 Zixuan Li , Jingtao Shi

We study solution methods for (strongly-)convex-(strongly)-concave Saddle-Point Problems (SPPs) over networks of two type - master/workers (thus centralized) architectures and meshed (thus decentralized) networks. The local functions at…

Optimization and Control · Mathematics 2022-08-23 Aleksandr Beznosikov , Gesualdo Scutari , Alexander Rogozin , Alexander Gasnikov

Independent learners are agents that employ single-agent algorithms in multi-agent systems, intentionally ignoring the effect of other strategic agents. This paper studies mean-field games from a decentralized learning perspective, with two…

Computer Science and Game Theory · Computer Science 2025-02-04 Bora Yongacoglu , Gürdal Arslan , Serdar Yüksel

The optimization problem of the minimum set of leaders for the controllability of undirected graphs are addressed. It is difficult to find not only its optimal solution but also its approximate algorithm. We propose a new concept, namely…

Optimization and Control · Mathematics 2021-12-03 Li Dai

This paper investigates the social optimality of linear quadratic mean field control systems with unmodeled dynamics. The objective of agents is to optimize the social cost, which is the sum of costs of all agents. By variational analysis…

Optimization and Control · Mathematics 2020-11-30 Bing-Chang Wang , Yong Liang

In this technical note, we consider the linear-quadratic time-inconsistent mean-field type leader-follower Stackelberg differential game with an adapted open-loop information structure. The objective functionals of the leader and the…

Optimization and Control · Mathematics 2019-11-12 Jun Moon , Hyun Jong Yang

This paper considers a leader-following problem for a group of heterogeneous linear time invariant (LTI) followers that are interacting over a directed acyclic graph. Only a subset of the followers has access to the state of the leader in…

Multiagent Systems · Computer Science 2019-11-21 Yi-Fan Chung , Solmaz S. Kia

In this paper, we study the social optimality for mean field linear quadratic control systems following the direct approach, where subsystems are coupled via individual dynamics and costs according to a network topology. A graph is…

Optimization and Control · Mathematics 2022-08-30 Yong Liang , Bingchang Wang , Huanshui Zhang

In this paper, the two-player leader-follower game with private inputs for feedback Stackelberg strategy is considered. In particular, the follower shares its measurement information with the leader except its historical control inputs…

Optimization and Control · Mathematics 2023-09-18 Yue Sun , Hongdan Li , Huanshui Zhang

We study incentive designs for a class of stochastic Stackelberg games with one leader and a large number of (finite as well as infinite population of) followers. We investigate whether the leader can craft a strategy under a dynamic…

Computer Science and Game Theory · Computer Science 2024-02-13 Sina Sanjari , Subhonmesh Bose , Tamer Başar