MLPro Documentations
v1.4.4
Home
MLPro - Machine Learning Professional
Welcome to MLPro
1. Introduction
2. Getting Started
Basic Functions
3. MLPro-BF - Basic Functions
Machine Learning
4. MLPro-SL - Supervised Learning
5. MLPro-OA - Online Adaptivity
6. MLPro-RL - Reinforcement Learning
6.1. Overview
6.2. Getting Started
6.3. Environments
6.3.1. Developing Custom Environments
6.3.2. Reusing Environment from the Pool
6.3.2.1. Bulk Good Laboratory Plant (BGLP)
6.3.2.2. Multi-Cartpole
6.3.2.3. Grid World
6.3.2.4. Robot Manipulator on Homogeneous Matrix
6.3.2.5. Double Pendulum
6.4. Agents
6.5. Scenarios
6.6. Training and Tuning
6.7. 3rd Party Support
7. MLPro-GT - Game Theory
Extension Hub
8. General Information
9. Third-Party Extensions
Appendices
A1 - Example Pool
A2 - API Reference
A3 - Project MLPro
MLPro Documentations
6.
MLPro-RL - Reinforcement Learning
6.3.
Environments
6.3.2.
Reusing Environment from the Pool
Edit on GitHub
6.3.2.
Reusing Environment from the Pool
6.3.2.1. Bulk Good Laboratory Plant (BGLP)
6.3.2.2. Multi-Cartpole
6.3.2.3. Grid World
6.3.2.4. Robot Manipulator on Homogeneous Matrix
6.3.2.5. Double Pendulum