mlgame3d-envs 0.1.1

Unity Machine Learning Agents Interface

Unity ML-Agents Python Interface

The mlagents_envs Python package is part of the ML-Agents Toolkit. mlagents_envs provides three Python APIs that allows direct interaction with the Unity game engine:

• A single agent API (Gym API)
• A gym-like multi-agent API (PettingZoo API)
• A low-level API (LLAPI)

The LLAPI is used by the trainer implementation in mlagents. mlagents_envs can be used independently of mlagents for Python communication.

Installation

Install the mlagents_envs package with:

python -m pip install mlagents_envs==1.1.0

Usage & More Information

See

• Gym API Guide
• PettingZoo API Guide
• Python API Guide

for more information on how to use the API to interact with a Unity environment.

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_envs uses localhost ports to exchange data between Unity and Python. As such, multiple instances can have their ports collide, leading to errors. Make sure to use a different port if you are using multiple instances of UnityEnvironment.
• Communication between Unity and the Python UnityEnvironment is not secure.
• On Linux, ports are not released immediately after the communication closes. As such, you cannot reuse ports right after closing a UnityEnvironment.