This is fascinating to me because I just recently built something similar (as a test), not for improving AI, instead it's for tuning hyperparameters for a physi

This is fascinating to me because I just recently built something similar (as a test), not for improving AI, instead it's for tuning hyperparameters for a physics simulation. We've managed to optimize execution of the simulation enough that brute-force search is a viable option, but giving an agent some background on how we tune those parameters on intuition and some physical reasoning, and a means to run tests and retrieve resulting statstics, works surprisingly well. I see it as essentially a hyperparameter search that is more capable of finding and exploiting implicit constraints in a system.