Why is the loss so high and my model is seemingly not learning anything on my reinforcement model for a 2d space

I have created a model that I adapted from this video:

https://www.youtube.com/watch?v=L8ypSXwyBds&t=3720s&pp=ygUecHl0b3JjaCByZWluZm9yY2VtZW50IGxlYXJuaW5n

The environment the model is working in is one with a controllable ball with tank-like controls, a ball that can be pushed and a square box that is the goal

The model gains rewards for touching the ball with the player and also gains rewards based on how close the ball is to the goal by the end of the iteration.

Additionally the model doesn’t seem to be learning anything

I’ve tried to Discretize the data,

I’ve tried adjusting the learning rate,

I’ve adjusted rewards (although I may not have adjusted them enough)

Still it doesn’t seem to learn anything,

I’m not sure if there’s a deep flaw in my model or perhaps the model isn’t well suited to the space as it was originally for snake in a grid-like space and this game is not built in a grid

Link to codebase:

https://github.com/jamiemitch121/RLNN-2D

submitted by /u/jam1211
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