Image de couverture de livre

Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zeng, Sihan, Bhatt, Sujay, Koppel, Alec, Ganesh, Sumitra
Format:	Preprint
Publié:	2024
Sujets:	Optimization and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to LLM Fine-Tuning
par: Zeng, Sihan, et autres
Publié: (2026)

Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis
par: Zeng, Sihan, et autres
Publié: (2025)

Partially Observable Contextual Bandits with Linear Payoffs
par: Zeng, Sihan, et autres
Publié: (2024)

Regularized Proportional Fairness Mechanism for Resource Allocation Without Money
par: Zeng, Sihan, et autres
Publié: (2025)

Learning Payment-Free Resource Allocation Mechanisms
par: Zeng, Sihan, et autres
Publié: (2023)

Convergence of Multi-Scale Reinforcement Q-Learning Algorithms for Mean Field Game and Control Problems
par: Angiuli, Andrea, et autres
Publié: (2023)

Accelerated Multi-Time-Scale Stochastic Approximation: Optimal Complexity and Applications in Reinforcement Learning and Multi-Agent Games
par: Zeng, Sihan, et autres
Publié: (2024)

Rethinking Neural Network Learning Rates: A Stackelberg Perspective
par: Zeng, Sihan, et autres
Publié: (2026)

Games with Rational and Herding Players
par: Vyas, Raghupati, et autres
Publié: (2026)

Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
par: Zeng, Sihan, et autres
Publié: (2021)

Open-Loop and Closed-Loop Strategies for Linear Quadratic Mean Field Games: The Direct Approach
par: Liang, Yong, et autres
Publié: (2025)

Convergence Analysis and Acceleration of Fictitious Play for General Mean-Field Games via the Best Response
par: Yu, Jiajia, et autres
Publié: (2024)

Finite State Mean Field Games with Common Shocks
par: Neumann, Berenice Anne, et autres
Publié: (2024)

Convergence of Actor-Critic Learning for Mean Field Games and Mean Field Control in Continuous Spaces
par: Fouque, Jean-Pierre, et autres
Publié: (2025)

Mean-Field Game for Gene Expression of Beetles
par: Jiang, Yiming, et autres
Publié: (2025)

Variational Contraction Conditions for Iterative Algorithms in Multi-Population Discrete-Time Regularized Mean-Field Games
par: Aydın, Uğur, et autres
Publié: (2026)

A Globally Convergent Flow for Time-Dependent Mean Field Games and a Solver-Agnostic Framework for Inverse Problems
par: Yan, Hanwei, et autres
Publié: (2026)

Convergence of Potential Mean-Field Games via Lyapunov Methods
par: Höfer, Felix
Publié: (2026)

On Discounted Infinite-Time Mean Field Games
par: Song, Yongsheng, et autres
Publié: (2025)

Discrete-Time Mean Field Type Games: Probabilistic Setup
par: Lambrecht, Grégoire, et autres
Publié: (2025)

$N$-Player Stochastic Differential Games with Regime Switching and Mean Field Convergence
par: Wang, Mingrui, et autres
Publié: (2025)

Approximation of Discrete-Time Infinite-Horizon Mean-Field Equilibria via Finite-Horizon Mean-Field Equilibria
par: Aydın, Uğur, et autres
Publié: (2025)

Analysis of Multiscale Reinforcement Q-Learning Algorithms for Mean Field Control Games
par: Angiuli, Andrea, et autres
Publié: (2024)

Evolutionary Analysis of Continuous-time Finite-state Mean Field Games with Discounted Payoffs
par: Pedroso, Leonardo, et autres
Publié: (2025)

Discrete Mean Field Games on Finite Graphs as Initial Value Optimization
par: Feng, Yaxin, et autres
Publié: (2026)

Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning
par: Zeng, Sihan, et autres
Publié: (2024)

A Single-Loop Gradient Algorithm for Pessimistic Bilevel Optimization via Smooth Approximation
par: Cao, Qichao, et autres
Publié: (2025)

Nonlinear Open-Loop Mean field Stackelberg Stochastic Differential Game
par: Huang, Jianhui, et autres
Publié: (2025)

Reinforcement Learning for Finite Space Mean-Field Type Games
par: Shao, Kai, et autres
Publié: (2024)

Approximate Equivariance in Reinforcement Learning
par: Park, Jung Yeon, et autres
Publié: (2024)

A Single-Loop Stochastic Gradient Algorithm for Minimax Optimization with Nonlinear Coupled Constraints
par: Cao, Qichao, et autres
Publié: (2026)

Sharpened Lazy Incremental Quasi-Newton Method
par: Lahoti, Aakash, et autres
Publié: (2023)

Mean-Field Games Under Model Uncertainty
par: Liang, Zongxia, et autres
Publié: (2026)

Mean Field Games of Control and Cryptocurrency Mining
par: Garcia, Nicolas, et autres
Publié: (2025)

Mean Field Games for Renewable Energy Development
par: Campi, Luciano, et autres
Publié: (2026)

Parallel-in-Time Preconditioning for Time-Dependent Variational Mean Field Games
par: Ljósheim, Heidi Wolles, et autres
Publié: (2025)

Mean Field Game and Control for Switching Hybrid Systems
par: C., Tejaswi K., et autres
Publié: (2024)

Mean Field Games with Reflected Dynamics
par: Jarni, Imane, et autres
Publié: (2025)

Modeling Epidemic Spread with Strategic Vaccination and Socialization: a Mean Field Game Analysis
par: Liu, Huaning, et autres
Publié: (2026)

Mean Field Games and Control on Large Expander Graphs
par: Zhang, Tao, et autres
Publié: (2026)