While poking around Google’s Machine Learning Crash Course, I found that they have released a TensorFlow library for building agents with deep reinforcement learning. This might be fun but I don’t know enough about the field to make use of that library yet. It also reminded me to take another look at game engine Unity 3D’s development in this area. A lot has happened!
I first took a quick glance at Unity ML-Agents more than two years ago. At the time, the project was still an experimental thing for Unity and a lot was still in flux. Since I didn’t know much about working in Unity or in reinforcement learning, that was too many variables in flux for my taste. A year later, Unity ML-Agents reached an official version 1.0, but it was still technically a preview technology. But not long after that they had become a “verified” package for use with Unity 2020.3 LTS build, signifying a mature tool. As part of being a verified package for use with Unity LTS, ML-Agents got some nice things like an official Unity technology landing page and a few pieces of curriculum have been posted to Unity Learn to help people get started.
The primary focus of Unity ML-Agents is for creating agents in the virtual world of a Unity game. Not necessarily for real-world robots which is where my interests lie. This is an important caveat because the Unity physics engine is not an accurate representation of the real world, and reinforcement learning agents are notorious for exploiting flaws in virtual engines to do “impossible” things. But that’s no reason to give up on Unity, which can still be a useful tool for robotics research. These caveats are just some tradeoffs amongst many more to keep in mind.
During this time that Unity evolved their ML-Agents library, I’ve occasionally dabbled in Unity with projects like Bouncy Bouncy Lights. I’m not bold enough to call myself a Unity developer yet, but I’m no longer completely overwhelmed by Unity editor user interface as I once were. I haven’t done much more in Unity because I haven’t felt particularly motivated to make games. But ML-Agents? That looks like pretty good motivation for me to put serious effort into understanding reinforcement learning.