The solution to my first quiz in the "Reinforcement Learning for Mechatronics Engineers and Optimal Control" course. It's not perfect but it works. There exists many unused functions and variables atm, this is due to us being short on time and thus unable to clear everything at the time of submitting.
@Moataz was my team mate for the quiz.
Just make sure that you have numpy, gymnasium, pyglet and pygame installed.
or simply use the following command:
pip install -U numpy gymnasium pyglet pygame
You could change the LEARNING_RATE, EPSILON, DISCOUNT, EPISODES, DISC_STEPS to modify the performance of the model. You could also implement an Epsilon decay model to prioritize the greedy action in the later episodes. Feel free to open a pull request with any modifications that would allow the algorithm to run better.
