Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目，它使游戏和模拟能够作为训练智能代理的环境。

unity3d unity unity-tech reinforcement-le deep-learning deep-reinforcement-learning neural-networks

文件历史

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
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mlagents/envs	Develop remove academy done (#2519)	5 年前
README.md	Split `mlagents` into two packages (#1812)	6 年前
setup.py	Develop allow python 3.7 (#2544)	5 年前

README.md

Unity ML-Agents Python Interface

The mlagents_envs Python package is part of the ML-Agents Toolkit. mlagents_envs provides a Python API that allows direct interaction with the Unity game engine. It is used by the trainer implementation in mlagents as well as the gym-unity package to perform reinforcement learning within Unity. mlagents_envs can be used independently of mlagents for Python communication.

The mlagents_envs Python package contains one sub package:

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.

Installation

Install the mlagents_envs package with:

pip install mlagents_envs

Usage & More Information

For more detailed documentation, check out the ML-Agents Toolkit documentation.