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

Jonathan Harper 7a0d1531 Fix subprocess model saving on Windows On Windows the interrupt for subprocesses works in a different way from OSX/Linux. The result is that child subprocesses and their pipes may close while the parent process is still running during a keyboard (ctrl+C) interrupt. To handle this, this change adds handling for EOFError and BrokenPipeError exceptions when interacting with subprocess environments. Additional management is also added to be sure when using parallel runs using the "num-runs" option that the threads for each run are joined and KeyboardInterrupts are handled. These changes made the "_win_handler" we used to specially manage interrupts on Windows unnecessary, so they have been removed.		6 年前
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mlagents/trainers	Fix subprocess model saving on Windows	6 年前
tests	Adds SubprocessUnityEnvironment for parallel envs (#1751)	6 年前
README.md	Fixing tables in documentation and other markdown errors. (#1199)	6 年前
setup.py	* Ticked API :	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.