Metadata-Version: 2.4
Name: mlagents-envs-aai
Version: 1.0.0
Summary: Unity Machine Learning Agents Interface
Home-page: https://github.com/Unity-Technologies/ml-agents
Author: Unity Technologies
Author-email: ML-Agents@unity3d.com
License: Apache-2.0
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.14
Description-Content-Type: text/markdown
Requires-Dist: grpcio
Requires-Dist: Pillow
Requires-Dist: protobuf
Requires-Dist: numpy
Requires-Dist: packaging
Provides-Extra: test
Requires-Dist: filelock; extra == "test"
Requires-Dist: pytest; extra == "test"
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Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
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# Unity ML-Agents Python Interface - Animal AI Fork

This is a fork of the ML-Agents Python package maintained by the Kinds of Intelligence team at [Leverhulme Centre for the Future of Intelligence](https://www.lcfi.ac.uk/) to support the [Animal-AI environment](https://github.com/Kinds-of-Intelligence-CFI/animal-ai). 

The `mlagents_envs` Python package is part of the
[ML-Agents Toolkit](https://github.com/Unity-Technologies/ml-agents).
`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:

```sh
python -m pip install mlagents_envs==1.1.0
```

## Usage & More Information

See
- [Gym API Guide](../com.unity.ml-agents/Documentation~/Python-Gym-API.md)
- [PettingZoo API Guide](../com.unity.ml-agents/Documentation~/Python-PettingZoo-API.md)
- [Python API Guide](../com.unity.ml-agents/Documentation~/Python-LLAPI.md)

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](https://docs.unity3d.com/Packages/com.unity.ml-agents@latest).

## 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`.
