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: 7a0d1531

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
..
mlagents/envs	Fix subprocess model saving on Windows	6 年前
README.md	Split `mlagents` into two packages (#1812)	6 年前
setup.py	Fix environment factory pickling on Windows (#1912)	6 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.