Using different Python libraries (OpenGL, Tensorflow, NEAT in the future) I am trying to make a working 2D balancing simulator, where a bouncing ball stays as close to target X line as possible.
- You have all necessary libraries installed They are written at the beginning of the file. I'll post a command to install them all soon
Not optimized version. Might have physics issues at large FPS (50+ I suppose). Supports only 1 ball at the time. AI gets ball position, velocity every few frames
Extended reward system to check more things e.g. how long does the ball spend in close proximity to the target
Sorted functions, it's easier to read and manage now. Now rewards data is saved along with the model. You can now simulate multiple pairs (ball & platform) at once! Simulation got optimized a little and works faster than previous versions. Title of the window displays current iteration and when was the last save.
Redesigned AI, now it collects info about last bounce instead of all the time. Reason - It should be rating the quality of last bounce, how well did the platform do in hitting the ball.
- AI tends to focus on one side (clockwise or anticlockwise turn all the time) and therefore resulting in a quick regression graph
- saved_modelsv4 - AI models are saved here, as well as reward stats so you can display the trend using
displayGraphv2.py - archive - previous generations are saved there
- File beginning with
mainand ending with[number].py- this is the main file you are supposed to start to train (and later use) the AI - You can also use
launchv[number].pywhich starts the main file