Generally the concept of hybrid algorithms is: - Half "hard maths" algorithms. i.e. cominbatorics, geometry, etc. - Half "fuzzy maths" algorithms. i.e. heuris

Generally the concept of hybrid algorithms is: - Half "hard maths" algorithms. i.e. cominbatorics, geometry, etc. - Half "fuzzy maths" algorithms. i.e. heuristics, approximation, machine learning. The idea being to solve the parts that can be easily solved by hard maths with those hard maths so that you can reduce the problem space for when you apply the fuzzy maths to solve the rest of the problem. In other words, it's taking the problem, breaking out discrete pieces to solve with well established hard maths, using heuristics & numerical solutions to tackle the remaining known problems without "easy" analytical solutions, then using ML to fill in all the gaps and glue the whole thing together.