Jianxun-Wang / PIMBRL
Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control
☆54Updated 2 years ago
Alternatives and similar repositories for PIMBRL:
Users that are interested in PIMBRL are comparing it to the libraries listed below
- Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms☆40Updated last year
- ☆10Updated 4 years ago
- We learn the dynamics model of a robot using a physics-informed neural network and use it to train a model-based RL algorithm.☆37Updated 10 months ago
- PyTorch Implementation of Lusch et al DeepKoopman☆13Updated 2 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆135Updated last year
- High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, T…☆12Updated 2 months ago
- An official 're'-implementation of Physics-induced graph neural network: An application to wind-farm power estimation (PGNN).☆27Updated 3 years ago
- Run MPC-based policies and train RL agents in gym-anm environments using implementations from Stable Baselines 3.☆12Updated 2 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。☆42Updated 4 years ago
- Pytorch Implementation of Deep Kalman Filter☆9Updated 2 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆39Updated 5 years ago
- Approximate dynamic programming (ADP) and Policy gradient (PG) based sequential optimal experimental design (sOED)☆20Updated 2 years ago
- ☆32Updated 4 months ago
- Master thesis spring 2019. Template to be futher used by the department of chemical engineering at NTNU,☆33Updated last year
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago
- Experiment code for "Continuous-Time Model-Based Reinforcement Learning"☆52Updated last year
- Data-driven Koopman control theory applied to reinforcement learning!☆32Updated last year
- This gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.☆26Updated last week
- Pytorch version of the MPC in model-based reinforcement learning (MBRL), currently only test in the CartPole-swing-up environment☆85Updated 4 years ago
- Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics.☆21Updated last year
- Official implementation for the NeurIPS 2023 paper: "Reduced Policy Optimization for Continuous Control with Hard Constraints"☆32Updated last year
- Gym Interface Wrapper for Simulink Models☆16Updated 2 months ago
- Code for "SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.☆113Updated 2 months ago
- Code for "On the Robustness of Safe Reinforcement Learning under Observational Perturbations" (ICLR 2023)☆46Updated 4 months ago
- PyTorch Implementation of Hamilton-Jacobi DQN☆16Updated 3 years ago
- Use deep learning to learn Koopman operator and LQR for optimal control☆16Updated 4 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- Reinforcement Learning Environments for Sustainable Energy Systems☆48Updated 10 months ago
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆83Updated 6 years ago