One possible way to compare constrained and unconstrained approaches is to have an RL agent find an optimal solution and then define constraints based on its violations.

“potentially but then compare them on the same task and that becomes difficult because the t because just designing a reward function which actually implicitly informs a specific constraint is difficult so maybe the probably would need to do kind of the other way around like you would need to have okay the RL agent actually figure out an optimal solution and then we need to go and and based on kind of”

“the the violation and so on you would need to define the constraints. But then of course you start off with the constraint on the back foot, because it basically needs to emulate the uh the unconstraint model. So it I think it's really hard to compare of whether it it makes a difference in”