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com.unity.ml-agents_1.0.0
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v0.1
ml-agents/ml-agents
GitHub
babe9e2f
Develop remove academy done (#2519)
* Initial Commit * Remove the Academy Done flag from the protobuf definitions * remove global_done in the environment * Removed irrelevant unitTests * Remove the max_step from the Academy inspector * Removed global_done from the python scripts * Modified and removed some tests * This actually does not break either curriculum nor generalization training * Replace global_done with reserved. Addressing Chris Elion's comment regarding the deprecation of the global_done field. We will use a reserved field to make sure the global done does not get replaced in the future causing errors. * Removed unused fake brain * Tested that the first call to step was the same as a reset call * black formating * Added documentation changes * Editing the migrating doc * Addressing comments on the Migrating doc * Addressing comments : - Removing dead code - Resolving forgotten merged conflicts - Editing documentations... |
5 年前 | |
|---|---|---|
| .. | ||
| mlagents/trainers | Develop remove academy done (#2519) | 5 年前 |
| README.md | Fixing tables in documentation and other markdown errors. (#1199) | 6 年前 |
| setup.py | Develop allow python 3.7 (#2544) | 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.