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We study policy gradient for mean-field control in continuous time in a reinforcement learning setting.
Multilayer feedforward networks are universal approximators
K. Hornik, M. Stinchcombe, and H. White · 1989
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The exact law of large numbers via fubini extension and characterization of insurable risks
Y. Sun · 2006
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Forward Backward stochastic differential equations and controlled McKean-Vlasov dynamics
R. Carmona and F. Delarue · 2015
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Mean field games and systemic risk
R. Carmona, J.-P. Fouque, and L. Sun · 2015
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Dynamic programming for optimal control of stochastic McKean-Vlasov dynamics
H. Pham and X. Wei · 2017
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Probabilistic Theory of Mean Field Games: vol. I, Mean Field FBSDEs, Control, and Games, Mean Field game with common noise and Master equations
R. Carmona and F. Delarue · 2018
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Probabilistic Theory of Mean Field Games: vol. II, Mean Field game with common noise and Master equations
R. Carmona and F. Delarue · 2018
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Smoothing properties of McKean–Vlasov SDEs
D. Crisan and E. McMurray · 2018
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Reinforcement Learning: An Introduction
R. Sutton and A. Barto · 2018
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A Weak Martingale Approach to Linear-Quadratic McKean-Vlasov Stochastic Control Problems
M. Basei and H. Pham · 2019
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Model-free mean-field reinforcement learning: mean-field MDP and mean-field Q-learning
R. Carmona, M. Laurière, and Z. Tan · 2019
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Linear-quadratic mean-field reinforcement learning: convergence of policy gradient methods
René Carmona, Mathieu Laurière, and Zongjun Tan · 2019
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On the convergence of model free learning in mean field games
R. Elie, J. Perolat, M. Laurière, M. Geist, and O. Pietquin · 2020
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Reinforcement learning in continuous time and space: A stochastic control approach
H. Wang, T. Zariphopoulou, and X. Y. Zhou · 2020
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Convergence analysis of machine learning algorithms for the numerical solution of mean-field control and games: II-the finite horizon case
R. Carmona and M. Laurière · 2021
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Policy gradient and actor critic learning in continuous time and space: theory and algorithms
Y. Jia and X. Y. Zhou · 2021
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A fest iterative PDE-based algorithm for feedback controls of nonsmooth mean-field control problems
C. Reisinger, W. Stockinger, and Y. Zhang · 2021
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Unified reinforcement Q-learning for mean field game and control problems
A. Angiuli, J-.P. Fouque, and M. Laurière · 2022
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A probabilistic approach to classical solutions of the master equation for large population equilibria
J.F. Chassagneux, D. Crisan, and F. Delarue · 2022
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Well-posedness for some non-linear SDEs and related PDE on the Wasserstein space
P.-E. Chaudru de Raynal and N. Frikha · 2022
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From the backward Kolmogorov PDE on the Wasserstein space to propagation of chaos for McKean-Vlasov SDEs
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Itô’s formula for flow of measures on semimartingales
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Policy evaluation and temporal difference learning in continuous time and space: a martingale approach
Y. Jia and X. Y. Zhou · 2021
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Numerical resolution of McKean-Vlasov FBSDEs using neural networks
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Entropy regularization for mean field games with learning
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Learning high-dimensional McKean-Vlasov forward-backward stochastic differential equations with general distribition dependence
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Mean-field neural networks-based algorithms for McKean-Vlasov control problems
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