pytorchrl
latest
Getting started:
Motivation
Installation
PyTorchRL API:
Agent Components
Actors
Algorithms
Off-policy
On-policy
Model-Based
Available Environments
Environment Vectors
Storage
Training Components
Tutorials:
Breaking down PyTorchRL
Create a custom environment
Code examples:
Simplified Code Examples
Unity 3D Obstacle Tower Environment
pytorchrl
»
Agent Components
»
Algorithms
Edit on GitHub
Algorithms
Off-policy
Double Deep Q-Learning (DDQN)
Deep Deterministic Policy Gradient (DDPG)
Twin Delayed Deep Deterministic (TD3)
Soft Actor Critic (SAC)
Maximum a Posteriori Policy Optimization (MPO)
On-policy
Advantage Actor Critic (A2C)
Proximal Policy Optimization (PPO)
Proximal Policy Optimization (PPO) with Random Network Distillation (RND)
Model-Based
Model Predictive Control (MPC) Random Shooting (RS)
Model Predictive Control (MPC) Cross-Entropy Method (CEM)
Model Predictive Control (MPC) Deep Dynamics Models (PDDM)
Read the Docs
v: latest
Versions
latest
stable
Downloads
On Read the Docs
Project Home
Builds