Physics-informed neural networks via stochastic Hamiltonian dynamics learning

In this paper, we propose novel learning frameworks to tackle optimal control problems by applying the Pontryagin maximum principle and then solving for a Hamiltonian dynamical system. Applying the Pontryagin maximum principle to the original optimal control problem shifts the learning focus to redu...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Bajaj, Chandrajit, Nguyen, Minh
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 26.04.2024
Subjects:	Learning Maximum principle Optimal control Robustness Stochastic models
ISSN:	2331-8422
Online Access:	Get full text
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