Approximating Optimal feedback Controllers of Finite Horizon Control Problems Using Hierarchical Tensor Formats (Q5084512)

scientific article; zbMATH DE number 7547920

Language	Label	Description	Also known as
English	Approximating Optimal feedback Controllers of Finite Horizon Control Problems Using Hierarchical Tensor Formats	scientific article; zbMATH DE number 7547920

Statements

instance of

scholarly article

0 references

title

Approximating Optimal feedback Controllers of Finite Horizon Control Problems Using Hierarchical Tensor Formats (English)

0 references

0 references

0 references

0 references

SIAM Journal on Scientific Computing

0 references

publication date

24 June 2022

0 references

full work available at URL

https://arxiv.org/abs/2104.06108

0 references

zbMATH Keywords

feedback control

0 references

Bellman equation

0 references

tensor train

0 references

Pontryagin maximum principle

0 references

model predictive control

0 references

policy iteration

0 references

describes a project that uses

xerus

0 references

ALEA

0 references

MaRDI profile type

MaRDI publication profile

0 references

cites work

Probabilistic max-plus schemes for solving Hamilton-Jacobi-Bellman equations

0 references

An Efficient Policy Iteration Algorithm for Dynamic Programming Equations

0 references

The Max-Plus Finite Element Method for Solving Deterministic Optimal Control Problems: Basic Properties and Convergence Analysis

0 references

Q4998939

0 references

An HJB-POD approach for the control of nonlinear PDEs on a tree structure

0 references

Optimal control and viscosity solutions of Hamilton-Jacobi-Bellman equations

0 references

On the Bellman equation for some unbounded control problems

0 references

Q3241581

0 references

Tensor networks and hierarchical tensors for the solution of high-dimensional partial differential equations

0 references

Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations

0 references

Feedback control methodologies for nonlinear systems

0 references

On the mathematical foundations of learning

0 references

Optimality, stability, and convergence in nonlinear control

0 references

Tensor Decomposition Methods for High-dimensional Hamilton--Jacobi--Bellman Equations

0 references

Overcoming the curse of dimensionality for some Hamilton-Jacobi partial differential equations via neural network architectures

0 references

Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

0 references

Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations

0 references

A numerical approach to the infinite horizon problem of deterministic control theory

0 references

Semi-Lagrangian Approximation Schemes for Linear and Hamilton—Jacobi Equations

0 references

A splitting algorithm for Hamilton-Jacobi-Bellman equations

0 references

Approximative Policy Iteration for Exit Time Feedback Control Problems Driven by Stochastic Differential Equations using Tensor Train Format

0 references

Stable als approximation in the TT-format for rank-adaptive tensor completion

0 references

A continuous analogue of the tensor-train decomposition

0 references

A regression-based Monte Carlo method to solve backward stochastic differential equations

0 references

Nonlinear model predictive control. Theory and algorithms

0 references

Model predictive control: Theory and practice - a survey

0 references

Numerical tensor calculus

0 references

A new scheme for the tensor representation

0 references

Algorithms for PDE-constrained optimization

0 references

Q3266141

0 references

The Alternating Linear Scheme for Tensor Optimization in the Tensor Train Format

0 references

On manifolds of tensors of fixed TT-rank

0 references

Tensor Spaces and Hierarchical Tensor Representations

0 references

Application of variational iteration method for Hamilton-Jacobi-Bellman equations

0 references

Polynomial Approximation of High-Dimensional Hamilton--Jacobi--Bellman Equations and Applications to Feedback Control of Semilinear Parabolic PDEs

0 references

Mitigating the curse of dimensionality: sparse grid characteristics method for optimal feedback control and HJB equations

0 references

Q3096060

0 references

Data-based approximate policy iteration for affine nonlinear continuous-time optimal control design

0 references

Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space

0 references

Adaptive Deep Learning for High-Dimensional Hamilton--Jacobi--Bellman Equations

0 references

Tensor-Train Decomposition

0 references

Breaking the Curse of Dimensionality, Or How to Use SVD in Many Dimensions

0 references

TT-cross approximation for multidimensional arrays

0 references

On some recent aspects of stochastic control and their applications

0 references

On the Convergence of Policy Iteration in Stationary Dynamic Programming

0 references

Q3285814

0 references

Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

0 references

Support Vector Machines

0 references

Tensor products of Sobolev-Besov spaces and applications to approximation from the hyperbolic cross

0 references

Optimal control: novel directions and applications

0 references

Actor-Critic Method for High Dimensional Static Hamilton--Jacobi--Bellman Partial Differential Equations based on Neural Networks

0 references

Identifiers

zbMATH Open document ID

1491.49021

0 references

DOI

10.1137/21M1412190

0 references

Mathematics Subject Classification ID

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

Sitelinks

Mathematics(1 entry)

mardi Publication:5084512