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com.unity.ml-agents_1.0.0
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v0.1
ml-agents/ml-agents
GitHub
0b5b1b01
Develop magic string + trajectory (#3122)
* added team id and identifier concat to behavior parameters * splitting brain params into brain name and identifiers * set team id in prefab * recieves brain_name and identifier on python side * added team id and identifier concat to behavior parameters * splitting brain params into brain name and identifiers * set team id in prefab * recieves brain_name and identifier on python side * rebased with develop * Correctly calls concatBehaviorIdentifiers * added team id and identifier concat to behavior parameters * splitting brain params into brain name and identifiers * set team id in prefab * recieves brain_name and identifier on python side * rebased with develop * Correctly calls concatBehaviorIdentifiers * trainer_controller expects name_behavior_ids * add_policy and create_policy separated * adjusting tests to expect trainer.add_policy to be called * fixing tests * fixed naming ... |
5 年前 | |
|---|---|---|
| .. | ||
| mlagents | Develop magic string + trajectory (#3122) | 5 年前 |
| README.md | Rename mlagents.envs to mlagents_envs (#3083) | 5 年前 |
| setup.py | Rename mlagents.envs to mlagents_envs (#3083) | 5 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-learnaccess 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.