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Copyright 2024 AlanLaboratory and individual contributors.

This product includes software developed by Unity Technologies under the Apache License, Version 2.0. You may obtain a copy of the License at:

http://www.apache.org/licenses/LICENSE-2.0

Modifications:

  • Adaptation from C# to C++: The original Unity ML-Agents C# code has been adapted to work in Unreal Engine with C++. The plugin integrates into Unreal Engine, enabling agent training similar to Unity.

  • Protobuf Definition: We have created our own Protobuf definitions for Python and C++ for Unreal Engine. This implementation supports Linux, Windows, and macOS.

  • Python Package (ml-agents-envs): The mlagents_envs Python package has been mostly copied from Unity ML-Agents, with changes to the Protobuf module import and SideChannel functionality due to engine differences.

  • Raycast Sensor: A Raycast sensor has been implemented for agent perception in Unreal Engine. The implementation is incomplete and differs from Unity's. Other sensor types have not yet been ported.

  • Blueprint Integration: Many methods have been adapted for Blueprint visual scripting, enabling easier use of the plugin within Unreal without needing extensive C++ knowledge.

Features Not Yet Implemented:

  • Inference Mode: Inference mode, which allows trained agents to be deployed in real-time without training, has not yet been implemented.

  • Unity Insight Analytics: Unity-specific Insight Analytics features have not been ported to Unreal. Significant adaptation is required due to reliance on Unity's infrastructure.

  • SideChannel Support: Unity's SideChannel communication system has not been ported. Given the architectural differences in Unreal, implementing this may require a different approach.

  • Sensors: Only the Raycast sensor has been implemented so far. Image-based observations (visual observations) and other sensor types are not yet supported, but visual observations are planned for future releases.

  • Unit Testing: Unit tests are currently missing. The goal is to replicate Unity’s unit tests in Unreal Engine and create a wide range of example environments, similar to Unity’s ML-Agents examples.

Future Goals:

  • We plan to expand sensor support, improve unit testing, and develop more example environments for Unreal Engine to mirror Unity's completeness.

  • Visual Observations support and more advanced features like inference mode and SideChannel communications are planned for future versions.

  • Additional support for Blueprint integration is also planned to enhance usability for developers without C++ expertise.

For development updates, planned features, and future releases, please refer to the project’s roadmap in the documentation.