1 citations · 1 across the 7 of their papers we have counts for
7 papers
Policy Gradient Learning for Distributionally Robust Markov Decision Processes under Wasserstein Ambiguity
Yadh Hafsi, Samy Mekkaoui, Huyên Pham +1
We study finite-horizon Markov decision processes under distributional uncertainty in the transition kernels and develop a policy-gradient framework for Wasserstein distributionall…
Actor-Critic Learning for Extended Mean Field Control with Deterministic Policies
Ziheng Cheng, Xin Guo, Huyên Pham +1
This paper develops a model-free reinforcement learning framework for continuous--time extended mean field control problems, where both the dynamics and reward may depend on the jo…
Discretization error from regularized Reinforcement Learning to continuous-time stochastic control
Huyên Pham, Yuming Paul Zhang, Yuhua Zhu
This paper establishes a rigorous connection between regularized discrete-time reinforcement learning (RL) and continuous-time stochastic optimal control. Specifically, classical R…
Model-free policy gradient for discrete-time mean-field control
Matthieu Meunier, Huyên Pham, Christoph Reisinger
We study model-free policy learning for discrete-time mean-field control (MFC) problems with finite state space and compact action space. In contrast to the extensive literature on…
Full error analysis of policy gradient learning algorithms for exploratory linear quadratic mean-field control problem in continuous time with common noise
Noufel Frikha, Huyên Pham, Xuanye Song
We consider reinforcement learning (RL) methods for finding optimal policies in linear quadratic (LQ) mean field control (MFC) problems over an infinite horizon in continuous time,…
Control randomisation approach for policy gradient and application to reinforcement learning in optimal switching
Robert Denkert, Huyên Pham, Xavier Warin
We propose a comprehensive framework for policy gradient methods tailored to continuous time reinforcement learning. This is based on the connection between stochastic control prob…
Actor critic learning algorithms for mean-field control with moment neural networks
Huyên Pham, Xavier Warin
We develop a new policy gradient and actor-critic algorithm for solving mean-field control problems within a continuous time reinforcement learning setting. Our approach leverages…