Rates of convergence for the policy iteration method for mean field games systems
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Publication:831502
DOI10.1016/j.jmaa.2022.126138zbMath1485.91019arXiv2108.00755OpenAlexW3190367256MaRDI QIDQ831502
Publication date: 23 March 2022
Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2108.00755
Mean field games and control (49N80) Mean field games (aspects of game theory) (91A16) Hamilton-Jacobi equations in optimal control and differential games (49L12)
Related Items (3)
Generalized conditional gradient and learning in potential mean field games ⋮ Policy iteration method for time-dependent mean field games systems with non-separable Hamiltonians ⋮ Learning Optimal Policies in Potential Mean Field Games: Smoothed Policy Iteration Algorithms
Cites Work
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- Global Properties of Transition Probabilities of Singular Diffusions
- Some Convergence Results for Howard's Algorithm
- On the Convergence of Policy Iteration in Stationary Dynamic Programming
- Proximal Methods for Stationary Mean Field Games with Local Couplings
- Convergence Properties of Policy Iteration
- Exponential Convergence and Stability of Howard's Policy Improvement Algorithm for Controlled Diffusions
- Large-Population Cost-Coupled LQG Problems With Nonuniform Agents: Individual-Mass Behavior and Decentralized $\varepsilon$-Nash Equilibria
- Mean Field Games and Mean Field Type Control Theory
- On L p Estimates and Regularity, I
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