[srean]

But what you describe is still curve fitting. I say this in spite of some expertise in ML myself. There are some parts of ML that are not fall in the curve fitting family but they are still a small part, for example Markov logic network, some parts of reinforcement learning.

What you are saying is curve fitting with good predictive ability is not trivial, and that is indeed true.

[salty_biscuits]

Markov Logic Networks are still about finding coefficients for a probability distribution over some process. My opinion is that there is only curve fitting. There is data and a minimum complexity model that can reproduce the data with minimum error. So do you really believe that there are physical processes where this approach will fail?

[srean]

There is more to Markov Logic than estimating parameters. That's the "unification" part of the Markov logic, the analogue of https://en.wikipedia.org/wiki/Unification_(computer_science)