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 11243348 Develop side channel (#2956 ) * [WIP] Side Channel initial layout * Working prototype for raw bytes * fixing format mistake * Added some errors and some unit tests in C# * Added the side channel for the Engine Configuration. (#2958) * Added the side channel for the Engine Configuration. Note that this change does not require modifying a lot of files : - Adding a sender in Python - Adding a receiver in C# - subscribe the receiver to the communicator (here is a one liner in the Academy) - Add the side channel to the Python UnityEnvironment (not represented here) Adding the side channel to the environment would look like such : ```python from mlagents.envs.environment import UnityEnvironment from mlagents.envs.side_channel.raw_bytes_channel import RawBytesChannel from mlagents.envs.side_channel.engine_configuration_channel import EngineConfigurationChannel channel0 = RawBytesChannel() channel1 = EngineConfigurationChannel() env = UnityEnvironme...		5 年前
..
mlagents/envs	Develop side channel (#2956)	5 年前
README.md	fix trailing whitespace in markdown (#2786)	5 年前
setup.py	Allow --version argument in mlagents-learn (#2942)	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.