Easier to solve the idealized general case first, so that you know what a solution even looks like, then adapt that to the real world with its many caveats.

And that's something that has happened, .or will happen, .or should happen? Well. It's not something that has happened. The best .AI isn't cut down ideal systems.

There are more benefits to MIRI's approach, such as: If you find that a certain kind of system cannot exist even in an ideal environment (such as a general Halting tester), you don't need to muck around with "implementable" solutions, never 

Negative results could be valuable but are far from guaranteed.