These problems aren't insurmountable. > We have trouble coming up with rule sets that are complete, That's okay. Incomplete rules are better than no rules at

These problems aren't insurmountable. > We have trouble coming up with rule sets that are complete, That's okay. Incomplete rules are better than no rules at all. There exist modeling techniques that require making less assumptions about the domain. For example, https://en.wikipedia.org/wiki/Nonparametric_statistics https://en.wikipedia.org/wiki/Nonparametric_statistics can deal with data sets about whose distribution you want to make no assumptions. Also, using an incomplete model and measuring its inadequacy can help us construct a better model. > non-contradictory, Contradictory rules are a fact of life in certain domains. There exist techniques for dealing with them, like https://en.wikipedia.org/wiki/Goal_programming https://en.wikipedia.org/wiki/Goal_programming. > and that really span the domain, You can split the domain into regions that you understand in isolation then patch everything together, possibly using some smoothening transformation to avoid pathological behaviors at the boundaries.