Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic Control

31 July 2021

Papers citing "Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic Control"

18 / 18 papers shown

Title
Multi-fidelity Reinforcement Learning Control for Complex Dynamical Systems Luning Sun Xin-Yang Liu Siyan Zhao Aditya Grover Jian-Xun Wang Jayaraman J. Thiagarajan AI4CE 21 0 0 08 Apr 2025
Sample-Efficient Reinforcement Learning of Koopman eNMPC Daniel Mayfrank M. Velioglu Alexander Mitsos Manuel Dahmen OffRL 36 0 0 24 Mar 2025
SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning Xuyang Li Romit Maulik 39 0 0 24 Feb 2025
How to Re-enable PDE Loss for Physical Systems Modeling Under Partial Observation Haodong Feng Yue Wang Dixia Fan AI4CE 75 0 0 12 Dec 2024
Physics-Informed Neural Networks with Skip Connections for Modeling and Control of Gas-Lifted Oil Wells Jonas Ekeland Kittelsen Eric A. Antonelo E. Camponogara Lars Struen Imsland PINN AI4CE 21 4 0 04 Mar 2024
Preconditioning for Physics-Informed Neural Networks Songming Liu Chang Su J. Yao Zhongkai Hao Hang Su Youjia Wu Jun Zhu AI4CE PINN 27 5 0 01 Feb 2024
Asynchronous Parallel Reinforcement Learning for Optimizing Propulsive Performance in Fin Ray Control Xin-Yang Liu Dariush Bodaghi Q. Xue Xudong Zheng Jian-Xun Wang 17 0 0 21 Jan 2024
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms Xiangyuan Zhang Weichao Mao S. Mowlavi M. Benosman Tamer Basar OffRL AI4CE 19 2 0 30 Nov 2023
A Mass-Conserving-Perceptron for Machine Learning-Based Modeling of Geoscientific Systems Yuan-Heng Wang Hoshin V. Gupta AI4CE 30 6 0 12 Oct 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 35 0 0 27 Sep 2023
A Survey on Physics Informed Reinforcement Learning: Review and Open Problems C. Banerjee Kien Nguyen Clinton Fookes M. Raissi PINN AI4CE 16 5 0 05 Sep 2023
Zero-Shot Wireless Indoor Navigation through Physics-Informed Reinforcement Learning Mingsheng Yin Tao Li Haozhe Lei Yaqi Hu S. Rangan Quanyan Zhu 11 6 0 11 Jun 2023
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations Franck Djeumou Cyrus Neary Ufuk Topcu DiffM 11 8 0 10 Jun 2023
Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs Stefan Werner Sebastian Peitz 20 9 0 14 Feb 2023
Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning Sebastian Peitz J. Stenner V. Chidananda Oliver Wallscheid Steven L. Brunton Kunihiko Taira AI4CE 14 17 0 25 Jan 2023
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning Kevin Zeng Alec J. Linot M. Graham AI4CE 15 28 0 01 May 2022
Physics-Informed Neural Nets for Control of Dynamical Systems Eric A. Antonelo E. Camponogara L. O. Seman Eduardo Rehbein de Souza J. Jordanou Jomi F. Hubner PINN AI4CE 17 62 0 06 Apr 2021
Deep Dynamics Models for Learning Dexterous Manipulation Anusha Nagabandi K. Konolige Sergey Levine Vikash Kumar 143 407 0 25 Sep 2019