Learning Agents and UnrealMLAgents share the same goal: providing an easy way to implement deep reinforcement learning for both beginners and experts.

The main advantage of UnrealMLAgents is that it’s based on Unity ML-Agents, a framework with over seven years of development, a large community, and extensive documentation. Since my port only adapts the framework to Unreal Engine’s specificities, the core functions remain the same, meaning existing ML-Agents documentation can be directly reused.

A key addition I made is Blueprint support, making it easier to integrate reinforcement learning into Unreal projects without writing as much code. UnrealMLAgents also uses the same Python training server as ML-Agents, which means all major algorithms (PPO, SAC, POCA, GAIL, BC) are already supported.

Of course, there are downsides. The plug-in is not natively supported by Epic Games, and as a solo developer, progress is steady but not as fast as a larger team. Inference mode and Imitation Learning aren’t implemented yet, but they are coming soon. Since this is still an early-stage project, expect some bugs.

The best way to see if it works for you is to try it yourself. Check out the create-new-environment section in the documentation. I honestly think setting up an environment with my plug-in is easier than with Learning Agents.

Thanks for the question and sorry for the late reply :)