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: 412dbe92

文件历史

Jonathan Harper d9a7e5b6 Fix failure on Academy Done() with parallel envs When using parallel SubprocessUnityEnvironment instances along with Academy Done(), a new step might be taken when reset should have been called because some environments may have been done while others were not (making "global done" less useful). This change manages the reset on `global_done` at the level of the environment worker, and removes the global reset from TrainerController.		6 年前
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mlagents/trainers	Fix failure on Academy Done() with parallel envs	6 年前
README.md	Fixing tables in documentation and other markdown errors. (#1199)	6 年前
setup.py	Python code reformat via [`black`](https://github.com/ambv/black).	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.