R itself is fine, it’s more about the Total Knowledge and how considering “more knowledge” to have 1000 items with 1% R (Total Knowledge = 10) than 9 with 100% (Total Knowledge = 9), sounds off to me, and it’s also why I think for the “minimum recommended” (which is in fact optimizing Total Knowledge) tends to just advice to lower R as much as possible.
Now, is it worth it to make it more complex ? Maybe, if that Optimal DR was really a huge huge deal (for example, if it’s used by future iteration of FSRS, smarter scheduler with varying DR, etc etc), but right now I feel this metric is not that important at this state, thus why I was even arguing about its current usefulness.
Also, the second point, how FSRS translate a DR=90% prediction into a 70% prediction, is indeed something that would need to be really improved before switching DR “on the fly”. (Or maybe not translating it, but using a more aggressive recency weight and train different parameters for different DRs, but that slightly contradicts finding a forgetting curve then)