If this is a duplicate, I apologize. I'm not really sure what to even search for to try and find a duplicate/answer!
We are working on a system for providing musical feedback to change the 'mood' of a subject. There are a number of parameters of the music that we can manipulate.
At the same time, we measure the physiology of the subject. I'm using a dynamic Bayesian network to reasonably accurately determine the level of frustration of the subject.
I'm looking for a way to, based on the level of frustration, tell the music generation mechanism "this set of parameters is effective", or not. The music parameters would then adjust automatically and iteratively, as we continue to make judgements of the subject's level of frustration.
I'd appreciate any pointers I can get! Please let me know if I can provide any clarification!