Jianxun-Wang / PIMBRL
Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control
☆45Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for PIMBRL
- We learn the dynamics model of a robot using a physics-informed neural network and use it to train a model-based RL algorithm.☆29Updated 5 months ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆37Updated 5 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆41Updated 3 years ago
- ☆10Updated 3 years ago
- High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, T…☆9Updated this week
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆42Updated 4 years ago
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆129Updated last year
- Approximate dynamic programming (ADP) and Policy gradient (PG) based sequential optimal experimental design (sOED)☆15Updated 2 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆29Updated last year
- Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms☆31Updated 7 months ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆84Updated last year
- Run MPC-based policies and train RL agents in gym-anm environments using implementations from Stable Baselines 3.☆11Updated last year
- Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…☆14Updated 7 months ago
- Pytorch Implementation of Deep Kalman Filter☆8Updated last year
- Use deep learning to learn Koopman operator and LQR for optimal control☆15Updated 4 years ago
- Gym Interface Wrapper for Simulink Models☆14Updated last year
- An official 're'-implementation of Physics-induced graph neural network: An application to wind-farm power estimation (PGNN).☆26Updated 3 years ago
- 这是一个关于基于模型的强化学习的资料，包括一些代码地址、paper、slide等。☆39Updated 4 years ago
- PyTorch Implementation of Hamilton-Jacobi DQN☆14Updated 3 years ago
- Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics.☆20Updated last year
- Consistent Koopman Autoencoders☆65Updated last year
- Master thesis spring 2019. Template to be futher used by the department of chemical engineering at NTNU,☆32Updated 10 months ago
- Experiment code for "Continuous-Time Model-Based Reinforcement Learning"☆47Updated 11 months ago
- Physics Informed Deep Learning for Traffic State Estimation: Illustrations with LWR and CTM Models☆13Updated last year
- Pytorch implementation of Model Predictive Control with learned models☆28Updated 4 years ago
- ☆57Updated 6 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆29Updated 2 years ago
- Pytorch version of the MPC in model-based reinforcement learning (MBRL), currently only test in the CartPole-swing-up environment☆77Updated 4 years ago
- ☆50Updated 2 months ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆58Updated 6 months ago