A change was made to the way the "train_mode" flag was used by environments when SubprocessUnityEnvironment was added which was intended to be part of a separate change set. This broke the CLI '--slow' flag. This change undoes those changes, so that the slow / fast simulation option works correctly. As a minor additional change, the remaining tests from top level 'tests' folders have been moved into the new test folders. |
5 年前 | |
---|---|---|
.. | ||
mlagents/trainers | Fix '--slow' flag after environment updates | 5 年前 |
README.md | Fixing tables in documentation and other markdown errors. (#1199) | 6 年前 |
setup.py | * Ticked API : | 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-learn
access 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.