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Unity ML-Agents Toolkit Documentation
Installation & Set-up
Getting Started
Creating Learning Environments
Advanced Usage
Training
- Training ML-Agents
- Using TensorBoard to Observe Training
- Training Using Concurrent Unity Instances
- Training with Proximal Policy Optimization
- Training with Soft Actor-Critic
- Training with Self-Play
Advanced Training Methods
- Training with Curriculum Learning
- Training with Imitation Learning
- Training with LSTM
- Training with Environment Parameter Randomization
Inference
Extending ML-Agents
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)
Translations
To make the Unity ML-Agents toolkit accessible to the global research and Unity developer communities, we're attempting to create and maintain translations of our documentation. We've started with translating a subset of the documentation to one language (Chinese), but we hope to continue translating more pages and to other languages. Consequently, we welcome any enhancements and improvements from the community.
Deprecated Docs
We no longer use them ourselves and so they may not be up-to-date. We've decided to keep them up just in case they are helpful to you.