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* Two deep reinforcement learning algorithms, [Proximal Policy Optimization](docs/Training-PPO.md) (PPO) and [Soft Actor-Critic](docs/Training-SAC.md) (SAC)
(PPO) and [Soft Actor-Critic](https://github.com/Unity-Technologies/ml-agents/tree/latest_release/docs/Training-SAC.md)
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(SAC)
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* Support for multiple environment configurations and training scenarios
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* Self-play mechanism for training agents in adversarial scenarios
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* Train memory-enhanced agents using deep reinforcement learning
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* Easily definable Curriculum Learning and Generalization scenarios
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* Built-in support for Imitation Learning
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## Documentation
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* For more information, in addition to installation and usage instructions, see
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our[documentation home](docs/Readme.md).
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the[documentation for the latest release](https://github.com/Unity-Technologies/ml-agents/tree/latest_release/docs/Readme.md).
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* If you are a researcher interested in a discussion of Unity as an AI platform, see a pre-print of our [reference paper on Unity and the ML-Agents Toolkit](https://arxiv.org/abs/1809.02627). Also, see below for instructions on citing this paper.
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* If you have used an earlier version of the ML-Agents toolkit, we strongly
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recommend our [guide on migrating from earlier versions](docs/Migrating.md).
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If you run into any other problems using the ML-Agents toolkit, or have a specific
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feature requests, please [submit a GitHub issue](https://github.com/Unity-Technologies/ml-agents/issues).
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Your opinion matters a great deal to us. Only by hearing your thoughts on the Unity ML-Agents Toolkit can we continue to improve and grow. Please take a few minutes to [let us know about it](https://github.com/Unity-Technologies/ml-agents/issues/1454).
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Your opinion matters a great deal to us. Only by hearing your thoughts on the Unity ML-Agents Toolkit can we continue
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to improve and grow. Please take a few minutes to [let us know about it](https://github.com/Unity-Technologies/ml-agents/issues/1454).
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For any other questions or feedback, connect directly with the ML-Agents
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