GitHub
ec278616
Hotfixes for Release 0.15.1 (#3698)
* [bug-fix] Increase height of wall in CrawlerStatic (#3650) * [bug-fix] Improve performance for PPO with continuous actions (#3662) * Corrected a typo in a name of a function (#3670) OnEpsiodeBegin was corrected to OnEpisodeBegin in Migrating.md document * Add Academy.AutomaticSteppingEnabled to migration (#3666) * Fix editor port in Dockerfile (#3674) * Hotfix memory leak on Python (#3664) * Hotfix memory leak on Python * Fixing * Fixing a bug in the heuristic policy. A decision should not be requested when the agent is done * [bug-fix] Make Python able to deal with 0-step episodes (#3671) * adding some comments Co-authored-by: Ervin T <ervin@unity3d.com> * Remove vis_encode_type from list of required (#3677) * Update changelog (#3678) * Shorten timeout duration for environment close (#3679) The timeout duration for closing an environment was set to the same duration as the timeout when waiting ... |
5 年前 | |
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mlagents | Hotfixes for Release 0.15.1 (#3698) | 5 年前 |
tests | [bug-fix] Fix issue with more than one continuous actions (#3547) | 5 年前 |
README.md | Rename mlagents.envs to mlagents_envs (#3083) | 5 年前 |
setup.py | Add 'run-experiment' script, simpler curriculum config (#3186) | 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.