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General Optimal control Problem Solver (GOPS), an easy-to-use PyTorch reinforcement learning solver package for industrial control.

Implantation of CtrlFormer

Code for Invariant Policy Optimization

Code for the paper Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer - ICML 2022

Google Research

Code for paper "Transfer RL across Observation Feature Spaces via Model-Based Regularization". https://openreview.net/forum?id=7KdAoOsI81C

A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.

A fast and differentiable model predictive control (MPC) solver for PyTorch.

Experiments with Deep Learning

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.

Leave No Trace is an algorithm for safe reinforcement learning.

萌新友好的，无需下载文件与配环境的，基于Github Actions的，P大学生出入校自动报备程序

Optimizing Dynamic Programming-Based Algorithms

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

Basic constrained RL agents used in experiments for the "Benchmarking Safe Exploration in Deep Reinforcement Learning" paper.

RL implementations

📈 如何用深度强化学习自动炒股

Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A Collection of Variational Autoencoders (VAE) in PyTorch.