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: 689765d6

文件历史

GitHub 689765d6 Modification of reward signals and rl_trainer for SAC (#2433 ) * Adds evaluate_batch to reward signals. Evaluates on minibatch rather than on BrainInfo. * Changes the way reward signal results are reported in rl_trainer so that we get the pure, unprocessed environment reward separate from the reward signals. * Moves end_episode to rl_trainer * Fixed bug with BCModule with RNN		6 年前
..
mlagents/trainers	Modification of reward signals and rl_trainer for SAC (#2433)	6 年前
README.md	Fixing tables in documentation and other markdown errors. (#1199)	6 年前
setup.py	Merge latest develop	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.