5 papers · 1 filter
Finite-Sample Metric Non-Collapse for Geometrically Supervised Latent World Models in Control
Alain Bensoussan, Minh-Nhat Phung, Minh-Binh Tran
We establish a finite-sample learning-to-control theory for geometrically supervised latent models of nonlinear deterministic systems. Geometric supervision is used only during tra…
Computational Control of Nonlinear Partial Differential Equations Using Machine Learning
Maximilian Kurbanov, Minh-Nhat Phung, Minh-Binh Tran
The numerical reconstruction of controls for nonlinear partial differential equations (PDEs) remains a challenging and relatively underdeveloped problem, despite the extensive lite…
Operator Splitting, Policy Iteration, and Machine Learning for Stochastic Optimal Control
Alain Bensoussan, Thien P. B. Nguyen, Minh-Binh Tran +1
We propose a splitting approach to solve the second-order Hamilton--Jacobi equation, reducing it to a heat step and a purely first-order step. The latter is implemented using a gra…
Controlling the Rates of a Chain of Harmonic Oscillators with a Point Langevin Thermostat
Amirali Hannani, Minh-Binh Tran, Minh Nhat Phung +1
We consider the control problem of controlling the rates of an infinite chain of coupled harmonic oscillators with a Langevin thermostat at the origin. We study the effect of two t…
Internal Control of The Transition Kernel for Stochastic Lattice Dynamics
Amirali Hannani, Minh-Nhat Phung, Minh-Binh Tran +1
In [5], we have designed impulsive and feedback controls for harmonic chains with a point thermostat. In this work, we study the internal control for stochastic lattice dynamics, w…