I've looked into policy gradient RL the last few months. As I find the topic quite interesting, I've been readings lots of papers about it. My aim is to write my master thesis in Maths about it. I already started out, the preliminary title being "Techniques for variance reduction in policy gradient reinforcement learning". Of course, I can sum up latest results, but a Master thesis' aim should be to create sth. new, or apply sth. to a new setting. Does anybody have an idea for a nice application? It was my idea to write the thesis in ML. My professor is not that much into ML but is happy to advise and evaluate the thesis.
Advice highly appreciated!