JeremyHahn comments on Progress on automated mathematical theorem proving? - Less Wrong
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|A kind of counter-example to your claim is the following: http://www.math.rutgers.edu/~zeilberg/GT.html It is an automated reasoning system for Euclidean geometry. Starting from literally nothing, it derived all of the geometric propositions in Euclid's Elements in a matter of seconds. Then it proceeded to produce a number of geometric theorems of human interest that were never noticed by any previous Euclidean geometers, classical or modern.
This is simply to point out that there are some fields of math that are classically very hard but computers find trivial. Another example is the verification of random algebraic identities by brute force.
On the other hand, large fields of mathematics have not yet come to be dominated by computers. For those I think this paper is a good introduction to some state-of-the-art, machine-learning based techniques: http://arxiv.org/abs/1108.3446 One can see from the paper that there is plenty of room for machine learning techniques to be ported from fields like speech and vision.
Progress in machine learning in vision and speech has recently been driven by the existence of huge training data-sets. It is only within the last few years that truly large databases of human-made proofs in things like set theory or group theory have been formalized. I think that future progress will come as these databases continue to grow.
This is interesting.
It's hard for me to assess it from the outside. In particular, I don't have a good sense for the number of sequences of logical derivations one has to consider in order to arrive at the theorems that were proved if one were to proceed by brute force. I find it more interesting that it honed in on classical theorems on its own than that it was able to prove them (one can use coordinate geometry to reduce proofs to solving polynomial equations).
I think that it's significant that Euclidean geometry fell out of fashion a long time ago: the fraction of modern mathematicians who think about Euclidean geometry is negligible, and this may reflect an accurate assessment of the field as mathematically shallow. I didn't appreciate geometry until I learned about discrete groups of isometries acting on homogeneous Riemannian manifolds.
Thanks for the reference
How much future progress? :-)
Where do you get these detailed claims about the program? I don't see anything like them in the book or here or here
Just to point out the obvious, your first link certainly does say that
Oh, yeah, I missed that Zeilberger used the phrase "from scratch," so that explains why JH says "from literally nothing" (though I disagree), but why did you quote the rest of the passage? Do you think it suggests any other of JH's claims?
I quoted the rest so that it was clear that the key phrase 'from scratch all the statements' was referring to a computational, implemented, software package for Euclidean / plane geometry in particular.