What does "close" mean here? I don't see that explained.
If you're trying to match outputs, then this is just old-fashioned GP with a minor twist - i.e. including speed in the fitness function, which has the potential to find some novel local maxima, which produce outputs that are close to the target AND very fast.
If you're trying to match instruction sequences - then I don't see the point at all.
GP often fails because it runs out of steam before producing a definitively correct solution.
It's easy to design cost/fitness functions that get close but not close enough, and slightly harder to design functions that solve a non-trivial problem some of the time.
It's incredibly hard to design functions that find an answer reliably without getting lost in the problem space.
