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: d771d99c

文件历史

GitHub fc6e8c35 [🐛🔨 ] Fix sac target for continuous actions (#5372 ) * Fix of the target entropy for continuous SAC * Lowering required steps of test and remove unecessary unsqueeze * Changing the target from -dim(a)^2 to -dim(a) by removing implicit broadcasting		4 年前
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mlagents	[🐛🔨 ] Fix sac target for continuous actions (#5372)	4 年前
tests	Automatically generate samples based on placement of mlagents-sample.json files in our examples. (#5077)	4 年前
README.md	Release 17 version bumps and docs version bumps (#5280)	4 年前
setup.py	Release 17 version bumps and docs version bumps (#5280)	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:

python -m pip install mlagents==0.26.0

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.