Is there a concept for comparing algorithms in artificial intelligence theory similar to reduction in complexity theory (Wikipedia)?
I'm asking this because I was wondering how AI algorithms are to be classified in terms of general applicability. As far as I'm aware, AI techniques are largely classified by which problem they are solving rather than how abstract/ general they are. To me, it would make sense to classify algorithms $P$ and $Q$ for different problems in terms of generality by determining whether $P$ can also—potentially by means of a prior transformation of the input—solve $Q$.
Articles and book references are very welcome!