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We address two major challenges in scientific machine learning (SciML): interpretability and computational efficiency. We increase the interpretability of certain learning processes by establishing a new theoretical connection between…

Machine Learning · Computer Science 2024-05-08 Paula Chen , Tingwei Meng , Zongren Zou , Jérôme Darbon , George Em Karniadakis

Hamilton-Jacobi (HJ) partial differential equations (PDEs) have diverse applications spanning physics, optimal control, game theory, and imaging sciences. This research introduces a first-order optimization-based technique for HJ PDEs,…

Numerical Analysis · Mathematics 2023-10-04 Tingwei Meng , Wenbo Hao , Siting Liu , Stanley J. Osher , Wuchen Li

Optimal control problems are crucial in various domains, including path planning, robotics, and humanoid control, demonstrating their broad applicability. The connection between optimal control and Hamilton-Jacobi (HJ) partial differential…

Optimization and Control · Mathematics 2024-03-06 Tingwei Meng , Siting Liu , Wuchen Li , Stanley Osher

A deep learning approach for the approximation of the Hamilton-Jacobi-Bellman partial differential equation (HJB PDE) associated to the Nonlinear Quadratic Regulator (NLQR) problem. A state-dependent Riccati equation control law is first…

Optimization and Control · Mathematics 2022-07-20 Anastasia Borovykh , Dante Kalise , Alexis Laignelet , Panos Parpas

Hamilton-Jacobi partial differential equations (HJ PDEs) play a central role in many applications such as economics, physics, and engineering. These equations describe the evolution of a value function which encodes valuable information…

Numerical Analysis · Mathematics 2026-01-01 Tingwei Meng , Siting Liu , Samy Wu Fung , Stanley Osher

We present a semi-real-time algorithm for minimal-time optimal path planning based on optimal control theory, dynamic programming, and Hamilton-Jacobi (HJ) equations. Partial differential equation (PDE) based optimal path planning methods…

Optimization and Control · Mathematics 2023-09-06 Christian Parkinson , Kyle Polage

We propose new and original mathematical connections between Hamilton-Jacobi (HJ) partial differential equations (PDEs) with initial data and neural network architectures. Specifically, we prove that some classes of neural networks…

Optimization and Control · Mathematics 2020-03-10 Jerome Darbon , Gabriel P. Langlois , Tingwei Meng

Maximum entropy reinforcement learning (RL) methods have been successfully applied to a range of challenging sequential decision-making and control tasks. However, most of existing techniques are designed for discrete-time systems. As a…

Optimization and Control · Mathematics 2020-09-29 Jeongho Kim , Insoon Yang

We present a method for optimal coordination of multiple vehicle teams when multiple endpoint configurations are equally desirable, such as seen in the autonomous assembly of formation flight. The individual vehicles' positions in the…

Robotics · Computer Science 2021-04-20 Matthew R. Kirchner , Mark J. Debord , João P. Hespanha

The Hamilton Jacobi Bellman Equation (HJB) provides the globally optimal solution to large classes of control problems. Unfortunately, this generality comes at a price, the calculation of such solutions is typically intractible for systems…

Optimization and Control · Mathematics 2014-09-23 Matanya B. Horowitz , Anil Damle , Joel W. Burdick

We develop a discrete analogue of Hamilton-Jacobi theory in the framework of discrete Hamiltonian mechanics. The resulting discrete Hamilton-Jacobi equation is discrete only in time. We describe a discrete analogue of Jacobi's solution and…

Optimization and Control · Mathematics 2011-08-15 Tomoki Ohsawa , Anthony M. Bloch , Melvin Leok

Presented is a method for efficient computation of the Hamilton-Jacobi (HJ) equation for time-optimal control problems using the generalized Hopf formula. Typically, numerical methods to solve the HJ equation rely on a discrete grid of the…

Systems and Control · Computer Science 2019-10-22 Matthew R. Kirchner , Gary Hewer , Jerome Darbon , Stanley Osher

We propose a novel numerical method for high dimensional Hamilton--Jacobi--Bellman (HJB) type elliptic partial differential equations (PDEs). The HJB PDEs, reformulated as optimal control problems, are tackled by the actor-critic framework…

Optimization and Control · Mathematics 2022-01-07 Mo Zhou , Jiequn Han , Jianfeng Lu

It is well known that time dependent Hamilton-Jacobi-Isaacs partial differential equations (HJ PDE), play an important role in analyzing continuous dynamic games and control theory problems. An important tool for such problems when they…

Optimization and Control · Mathematics 2016-05-09 Jérôme Darbon , Stanley Osher

In this paper, we propose Q-learning algorithms for continuous-time deterministic optimal control problems with Lipschitz continuous controls. Our method is based on a new class of Hamilton-Jacobi-Bellman (HJB) equations derived from…

Machine Learning · Computer Science 2020-10-28 Jeongho Kim , Jaeuk Shin , Insoon Yang

Systems of Hamilton-Jacobi equations arise naturally when we study the optimal control problems with pathwise deterministic trajectories with random switching. In this work, we are interested in the large time behavior of weakly coupled…

Analysis of PDEs · Mathematics 2013-11-19 Vinh Duc Nguyen

We design fast numerical methods for Hamilton-Jacobi equations in density space (HJD), which arises in optimal transport and mean field games. We overcome the curse-of-infinite-dimensionality nature of HJD by proposing a generalized Hopf…

Numerical Analysis · Mathematics 2018-05-07 Yat Tin Chow , Wuchen Li , Stanley Osher , Wotao Yin

Hamilton-Jacobi (HJ) reachability analysis is a widely used method for ensuring the safety of robotic systems. Traditional approaches compute reachable sets by numerically solving an HJ Partial Differential Equation (PDE) over a grid, which…

Robotics · Computer Science 2025-05-08 Zeyuan Feng , Le Qiu , Somil Bansal

In this paper we study a class of HJB equations which solve for equilibria for general time-inconsistent deterministic linear quadratic control problems within the intra-personal game theoretic framework, where the inconsistency arises from…

Optimization and Control · Mathematics 2025-05-21 Yunfei Peng , Wei Wei

This paper presents a mathematical formulation to perform temporal parallelisation of continuous-time optimal control problems, which can be solved via the Hamilton--Jacobi--Bellman (HJB) equation. We divide the time interval of the control…

Optimization and Control · Mathematics 2024-12-18 Simo Särkkä , Ángel F. García-Fernández
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