ml-agents/docs

Unity ML-Agents Toolkit Documentation

Installation & Set-up

• Installation
  • Background: Jupyter Notebooks
  • Docker Set-up
  • Using Virtual Environment
• Basic Guide

Getting Started

• ML-Agents Toolkit Overview
  • Background: Unity
  • Background: Machine Learning
  • Background: TensorFlow
• Getting Started with the 3D Balance Ball Environment
• Example Environments

Creating Learning Environments

• Making a New Learning Environment
• Designing a Learning Environment
  • Agents
  • Academy
  • Brains: Player, Heuristic, Learning
• Learning Environment Best Practices

Advanced Usage

• Using the Monitor
• Using the Video Recorder
• Using an Executable Environment
• Creating Custom Protobuf Messages

Training

• Training ML-Agents
• Using TensorBoard to Observe Training
• Training with Proximal Policy Optimization
• Training with Soft Actor-Critic

Advanced Training Methods

• Training with Curriculum Learning
• Training with Imitation Learning
• Training with LSTM
• Training Generalized Reinforcement Learning Agents
• Training Using Concurrent Unity Instances

Cloud Training

• Training on the Cloud with Amazon Web Services
• Training on the Cloud with Microsoft Azure

Inference

• Unity Inference Engine

Help

• Migrating from earlier versions of ML-Agents
• Frequently Asked Questions
• ML-Agents Glossary
• Limitations

API Docs

• API Reference
• How to use the Python API
• Wrapping Learning Environment as a Gym (+Baselines/Dopamine Integration)
• Creating custom protobuf messages