Thoughts on parameter optimisation.

I'm currently trying out building a pacman game using MDP - I've built all the functions but I'm struggling to get a consistent good score (above 2000). Adjusting my point system is the only way to get a difference in scores. The parameters/variables i'm mentioning include, Capsules, food, ghosts (scarred or not), the distance from the ghost) - so something like food = 10 points, capsules = 20 points etc.

Instead of mindlessly going back and forth changing parameters and testing them out. Is there a way I can use machine learning to provide the best combination of parameters? I've looked into using the gym package as a start but I was wondering if anyone had any other idea they can suggest.