Alternatives and similar repositories for PIMBRL:

Users that are interested in PIMBRL are comparing it to the libraries listed below

• wgshen / sOED
  Approximate dynamic programming (ADP) and Policy gradient (PG) based sequential optimal experimental design (sOED)
  ☆20Updated 2 years ago
• adi3e08 / Physics_Informed_Model_Based_RL
  We learn the dynamics model of a robot using a physics-informed neural network and use it to train a model-based RL algorithm.
  ☆36Updated 9 months ago
• Pdbz199 / koopman-rl
  High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, T…
  ☆11Updated 2 months ago
• weishiyan / Physics-Informed-Reinforcement-Learning
  ☆10Updated 4 years ago
• xiangyuan-zhang / controlgym
  Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
  ☆39Updated last year
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆47Updated 3 years ago
• mlpotter / DeepKoopmanLusch
  PyTorch Implementation of Lusch et al DeepKoopman
  ☆13Updated 2 years ago
• emedd33 / Reinforcement-Learning-in-Process-Control
  Master thesis spring 2019. Template to be futher used by the department of chemical engineering at NTNU,
  ☆32Updated last year
• ZhongZ-Wang / Model-Based-RL
  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。
  ☆41Updated 4 years ago
• SimonRennotte / Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control
  Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…
  ☆134Updated last year
• wadx2019 / rpo
  Official implementation for the NeurIPS 2023 paper: "Reduced Policy Optimization for Continuous Control with Hard Constraints"
  ☆32Updated last year
• johbrust / simulink_gym
  Gym Interface Wrapper for Simulink Models
  ☆16Updated last month
• robinhenry / gym-anm-exp
  Run MPC-based policies and train RL agents in gym-anm environments using implementations from Stable Baselines 3.
  ☆11Updated 2 years ago
• drgona / PIML_ACC2023
  Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…
  ☆19Updated 11 months ago
• NoulliCHEN / PIDAO
  ☆29Updated 4 months ago
• Junyoungpark / PGNN
  An official 're'-implementation of Physics-induced graph neural network: An application to wind-farm power estimation (PGNN).
  ☆28Updated 3 years ago
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆45Updated 4 years ago
• matthias-weissenbacher / KFC
  Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics.
  ☆21Updated last year
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆45Updated last year
• BYU-PRISM / Transformer_MPC
  ☆37Updated last year
• Jonas-Nicodemus / PINNs-based-MPC
  We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…
  ☆99Updated last year
• liuzuxin / safe-rl-robustness
  Code for "On the Robustness of Safe Reinforcement Learning under Observational Perturbations" (ICLR 2023)
  ☆46Updated 3 months ago
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆38Updated 5 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆58Updated 2 years ago
• cagatayyildiz / oderl
  Experiment code for "Continuous-Time Model-Based Reinforcement Learning"
  ☆52Updated last year
• rozenk30 / Quantitative-Comparison-of-RL-and-MPC
  Codes for "Quantitative Comparison of Reinforcement Learning and Data-driven Model Predictive Control for Chemical and Biological Process…
  ☆11Updated last year
• chennnnnyize-zz / Optimal-Control-via-Neural-Networks
  Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach
  ☆80Updated 6 years ago
• tony23545 / DeepKoopman
  Use deep learning to learn Koopman operator and LQR for optimal control
  ☆16Updated 4 years ago
• AgrawalAmey / safe-explorer
  Pytorch implementation of "Safe Exploration in Continuous Action Spaces" [Dalal et al.]
  ☆70Updated 5 years ago
• Pdbz199 / Koopman-RL-Old
  Data-driven Koopman control theory applied to reinforcement learning!
  ☆31Updated last year