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

目录树: bf9ad53e

文件历史

Miguel Alonso Jr 11984db2 Added local precommit hook to autogenerate markdown documentation using pydoc-markdown		4 年前
..
mlagents_envs	Fixed pre-commit issues with docstrings in mlagents-env base_env	4 年前
README.md	Release 17 version bumps and docs version bumps (#5280)	4 年前
pydoc-config.yaml	Added local precommit hook to autogenerate markdown documentation using pydoc-markdown	4 年前
setup.py	Clarify Python 3.8 support (#4784)	4 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.

Installation

Install the mlagents_envs package with:

python -m pip install mlagents_envs==0.26.0

Usage & More Information

See the Python API Guide for more information on how to use the API to interact with a Unity environment.

For more information on the ML-Agents Toolkit and how to instrument a Unity scene with the ML-Agents SDK, check out the main ML-Agents Toolkit documentation.

Limitations

mlagents_envs uses localhost ports to exchange data between Unity and Python. As such, multiple instances can have their ports collide, leading to errors. Make sure to use a different port if you are using multiple instances of UnityEnvironment.
Communication between Unity and the Python UnityEnvironment is not secure.
On Linux, ports are not released immediately after the communication closes. As such, you cannot reuse ports right after closing a UnityEnvironment.