Vincent-Pierre BERGES
bc636075
API for sending custom protobuf messages to and from Unity. (#1595)
* API for sending custom protobuf messages to and from Unity. * Rename custom_output to custom_outputs. * Move custom protos to their own files. * Add SetCustomOutput method. * Add docstrings. * Various adjustments. * Rename CustomParameters -> CustomResetParameters * Rename CustomOutput -> CUstomObservation * Add CustomAction * Add CustomActionResult * Remove custom action result. * Remove custom action result from Python API * Start new documentation. * Add some docstrings * Expand documentation. * Typos * Tweak doc. Also eliminate GetCustomObservation. * Fix typo. * Clarify docs. * Remove trailing whitspace |
6 年前 | |
---|---|---|
.. | ||
mlagents | API for sending custom protobuf messages to and from Unity. (#1595) | 6 年前 |
tests | Merge pull request #1765 from Unity-Technologies/release-v0.7 | 6 年前 |
README.md | Fixing tables in documentation and other markdown errors. (#1199) | 6 年前 |
setup.py | Ticked API : (#1696) | 6 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.