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

GitHub 87a30e34 Support both 32-bit and 64-bit types in UnityEnvironment (#1471 ) We check for the single brain case in UnityEnvironment by checking for applicable non-dict types in the step arguments. However for ints and floats we just use `np.int_` and `np.float_` for the check, which are the defaults for your system. This means if you are using an application (like baselines in #1448) which uses the wrong int/float size an error will be thrown. This change explicitly allows both 32 and 64-bit numbers.		6 年前
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mlagents	Support both 32-bit and 64-bit types in UnityEnvironment (#1471)	6 年前
tests	Merge pull request #1470 from Unity-Technologies/release-v0.6-make-test-directory-agnostic	6 年前
README.md	Fixing tables in documentation and other markdown errors. (#1199)	6 年前
requirements.txt	New proto files	7 年前
setup.py	Fixing learn.py, trainer_controller.py, and Docker (#1164)	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.