29 citations · 119 across the 29 of their papers we have counts for
5 papers · 1 filter
Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces
Andrea Angiuli, Jean-Pierre Fouque, Ruimeng Hu +1
We present the development and analysis of a reinforcement learning (RL) algorithm designed to solve continuous-space mean field game (MFG) and mean field control (MFC) problems in…
Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms
Robert Balkin, Hector D. Ceniceros, Ruimeng Hu
In this paper, we propose a numerical methodology for finding the closed-loop Nash equilibrium of stochastic delay differential games through deep learning. These games are prevale…
Directed Chain Generative Adversarial Networks
Ming Min, Ruimeng Hu, Tomoyuki Ichiba
Real-world data can be multimodal distributed, e.g., data describing the opinion divergence in a community, the interspike interval distribution of neurons, and the oscillators nat…
Recent Developments in Machine Learning Methods for Stochastic Control and Games
Ruimeng Hu, Mathieu Laurière
Stochastic optimal control and games have a wide range of applications, from finance and economics to social sciences, robotics, and energy management. Many real-world applications…
Pathwise Solutions for Stochastic Hydrostatic Euler Equations under the Local Rayleigh Condition
Ruimeng Hu, Quyuan Lin
The hydrostatic Euler equations are important in the study of atmospheric and oceanic dynamics in the planetary scale. While its deterministic version has been widely studied in th…