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: 411b0a19

文件历史

Andrew Cohen 411b0a19 reuse action dict in torch policy for pre_action		4 年前
..
mlagents	reuse action dict in torch policy for pre_action	4 年前
tests	removed action_spec.size	4 年前
README.md	[refactor] Store and restore state along with checkpoints (#4025)	5 年前
setup.py	[MLA-1519] Don't mark action_probs as an output node. (#4613)	4 年前

README.md

Unity ML-Agents Trainers

The mlagents Python package is part of the ML-Agents Toolkit. mlagents provides a set of reinforcement and imitation learning algorithms designed to be used with Unity environments. The algorithms interface with the Python API provided by the mlagents_envs package. See here for more information on mlagents_envs.

The algorithms can be accessed using the: mlagents-learn access point. See here for more information on using this package.

Installation

Install the mlagents package with:

pip3 install mlagents

Usage & More Information

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 does not yet explicitly support multi-agent scenarios so training cooperative behavior among different agents is not stable.
Resuming self-play from a checkpoint resets the reported ELO to the default value.