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com.unity.ml-agents_1.0.0
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v0.1
ml-agents/ml-agents
GitHub
78f4da76
Making Gym a wrapper (#3812)
* Making Gym a wrapper * Readding no graphics to the run gym test * typo * Modifying the changelog and the migrating doc * Applying pre-commit * [skip ci] Update gym-unity/gym_unity/tests/test_gym.py Co-Authored-By: Chris Elion <chris.elion@unity3d.com> * Adding a note that the BaseEnv will close when the wrapper closes * FoRgOt To rUn PrE-ComMiT Co-authored-by: Chris Elion <chris.elion@unity3d.com> |
5 年前 | |
|---|---|---|
| .. | ||
| mlagents | [bug-fix] Increase buffer size for SAC tests (#3813) | 5 年前 |
| tests | Making Gym a wrapper (#3812) | 5 年前 |
| README.md | Rename mlagents.envs to mlagents_envs (#3083) | 5 年前 |
| setup.py | Removing the notebooks from the github repository. (#3704) | 5 年前 |
README.md
Unity ML-Agents Python Interface and Trainers
The mlagents Python package is part of the
ML-Agents Toolkit.
mlagents provides a Python API that allows direct interaction with the Unity
game engine as well as a collection of trainers and algorithms to train agents
in Unity environments.
The mlagents Python package contains two sub packages:
-
mlagents_envs: A low level API which allows you to interact directly with a Unity Environment. See here for more information on using this package. -
mlagents.trainers: A set of Reinforcement Learning algorithms designed to be used with Unity environments. Access them using the:mlagents-learnaccess point. See here for more information on using this package.
Installation
Install the mlagents package with:
pip install mlagents
Usage & More Information
For more detailed documentation, check out the ML-Agents Toolkit documentation.