Digital Twin Calibration with Model-Based Reinforcement Learning

4 January 2025

Papers citing "Digital Twin Calibration with Model-Based Reinforcement Learning"

24 / 24 papers shown

Title
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs Dongsheng Ding Chen-Yu Wei Kai Zhang Alejandro Ribeiro 99 22 0 20 Jun 2023
Optimal Exploration for Model-Based RL in Nonlinear Systems Andrew Wagenmaker Guanya Shi Kevin Jamieson 79 15 0 15 Jun 2023
Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell Bioreactors Tianqi Cui Tom S. Bertalan Nelson Ndahiro Pratik Khare Michael Betenbaugh C. Maranas Ioannis G. Kevrekidis 21 8 0 05 May 2023
Variance Reduction based Experience Replay for Policy Optimization Hua Zheng Wei Xie M. Feng OffRL 70 2 0 17 Oct 2021
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration Yuda Song Wen Sun 107 21 0 15 Jul 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 88 1,209 0 20 May 2021
Policy Optimization in Dynamic Bayesian Network Hybrid Models of Biomanufacturing Processes Hua Zheng Wei Xie I. Ryzhov D. Xie OffRL 15 7 0 13 May 2021
Task-Optimal Exploration in Linear Dynamical Systems Andrew Wagenmaker Max Simchowitz Kevin Jamieson 77 18 0 10 Feb 2021
Biomanufacturing Harvest Optimization with Small Data Bo Wang Wei Xie Tugce G. Martagan A. Akçay Bram van Ravenstein 118 5 0 11 Jan 2021
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes Dongruo Zhou Quanquan Gu Csaba Szepesvári 86 209 0 15 Dec 2020
Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging Enrui Zhang Minglang Yin George Karniadakis 73 66 0 02 Sep 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 96 305 0 01 Jun 2020
MOReL : Model-Based Offline Reinforcement Learning Rahul Kidambi Aravind Rajeswaran Praneeth Netrapalli Thorsten Joachims OffRL 107 677 0 12 May 2020
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems Yashwanth Kumar Nakka Anqi Liu Guanya Shi Anima Anandkumar Yisong Yue Soon-Jo Chung 107 49 0 09 May 2020
A Finite Time Analysis of Two Time-Scale Actor Critic Methods Yue Wu Weitong Zhang Pan Xu Quanquan Gu 177 149 0 04 May 2020
Physics-Informed Neural Networks for Power Systems George S. Misyris Andreas Venzke Spyros Chatzivasileiadis PINN AI4CE 69 221 0 09 Nov 2019
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling Yuping Luo Huazhe Xu Tengyu Ma SSL 72 13 0 12 Jul 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 111 560 0 11 Jul 2019
Tight Analyses for Non-Smooth Stochastic Gradient Descent Nicholas J. A. Harvey Christopher Liaw Y. Plan Sikander Randhawa 73 138 0 13 Dec 2018
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation Jalaj Bhandari Daniel Russo Raghav Singal 113 340 0 06 Jun 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Kurtland Chua Roberto Calandra R. McAllister Sergey Levine BDL 230 1,284 0 30 May 2018
Model-Ensemble Trust-Region Policy Optimization Thanard Kurutach I. Clavera Yan Duan Aviv Tamar Pieter Abbeel 84 453 0 28 Feb 2018
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification Max Simchowitz Horia Mania Stephen Tu Michael I. Jordan Benjamin Recht 76 342 0 22 Feb 2018
Computer Model Calibration using the Ensemble Kalman Filter D. Higdon M. Pratola J. Gattiker E. Lawrence Salman Habib K. Heitmann Steve Price C. Jackson M. Tobis 42 31 0 16 Apr 2012