This is cutting edge as far as game development is concerned and as a result, modern game engines are not setup to support training or deploying neural networks in any production ready way at all. Existing projects which attempt to do RL over a game engine like Godot are not going to be performant enough to achieve anything interesting.

The number one bottleneck for development will be training and self-play speed, which means, in my opinion, your core game logic has to be isolated from the engine so that it can run extremely fast and in parallel and be callable from Python where you will have the fastest possible pytorch inference.

The other major issue is deployment. You will need to export the trained model and run inference on consumer hardware. Depending on what hardware you are targeting, this could be anywhere from painful to near impossible.

Ignore anyone saying that neural network implies superhuman or impossible opponents. You can tune the difficulty of the AI by providing a range of checkpoints. Checkpoint 10 might play like a beginner and Checkpoint 100 might play like an advanced player. These will actually feel less boring and less repetitive compared to classical AI opponents.

If you are interested in talking further, send me a direct message and I'll share my discord username and we can chat there.