31 citations · 84 across the 12 of their papers we have counts for
5 papers · 1 filter
Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems
Ethan N. Evans, Marcus A. Pereira, George I. Boutselis +1
Systems involving Partial Differential Equations (PDEs) have recently become more popular among the machine learning community. However prior methods usually treat infinite dimensi…
Deep Forward-Backward SDEs for Min-max Control
Ziyi Wang, Keuntaek Lee, Marcus A. Pereira +2
This paper presents a novel approach to numerically solve stochastic differential games for nonlinear systems. The proposed approach relies on the nonlinear Feynman-Kac theorem tha…
Deep 2FBSDEs For Systems With Control Multiplicative Noise
Marcus A Pereira, Ziyi Wang, Tianrong Chen +2
We present a deep recurrent neural network architecture to solve a class of stochastic optimal control problems described by fully nonlinear Hamilton Jacobi Bellmanpartial differen…
Leveraging Stochasticity for Open Loop and Model Predictive Control of Complex Fluid Systems
George I. Boutselis, Ethan N. Evans, Marcus A. Pereira +1
Stochastic Spatio-Temporal processes are prevalent across domains ranging from modeling of plasma to the turbulence in fluids to the wave function of quantum systems. This letter s…
Learning Deep Stochastic Optimal Control Policies using Forward-Backward SDEs
Marcus Pereira, Ziyi Wang, Ioannis Exarchos +1
In this paper we propose a new methodology for decision-making under uncertainty using recent advancements in the areas of nonlinear stochastic optimal control theory, applied math…