The best way to get a sense of the state of the art in automated theorem
proving would be to download and play with the systems

http://en.wikipedia.org/wiki/Isabelle_(theorem_prover)

and

http://en.wikipedia.org/wiki/Prover9

, which are state-of-the-art automated theorem provers.

Isabelle is fairly close to how theorem-proving would be done in PLN, if one
suppressed uncertainty and used only crisp truth values, and didn't try
anything funky with experience-based inference control.

Prover9 is different as it uses some special normal forms to represent
theorems (Skolemizing out all existential quantifiers, for instance).

I don't know these systems well, but I played with HOL and Otter, which were
the predecessors to these two systems.

Looking at the publications by the folks involved with these projects will
give you a sense for the state of the art.

-- Ben G


On Thu, Oct 16, 2008 at 11:50 PM, Abram Demski <[EMAIL PROTECTED]>wrote:

> "Your intuition is dead wrong based on the last decades of work in
> automated theorem proving!!"
>
> Ben,
>
> Thanks... though I do find that rather strange... can you cite any
> particular references?
>
> The reason I find it surprising, is that it suggests the existence of
> actual shortcuts, rather than only heuristics that work in the domains
> we're interested in but which become useless on random problems. If
> these shortcuts exist, I wonder, could they be enumerated by some
> brute-force method?
>
> --Abram
>
> On Thu, Oct 16, 2008 at 11:26 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote:
> >
> >
> > On Thu, Oct 16, 2008 at 11:21 PM, Abram Demski <[EMAIL PROTECTED]>
> > wrote:
> >>
> >> On Thu, Oct 16, 2008 at 10:32 PM, Dr. Matthias Heger <[EMAIL PROTECTED]>
> >> wrote:
> >> > In theorem proving computers are weak too compared to performance of
> >> > good
> >> > mathematicians.
> >>
> >> I think Ben asserted this as well (maybe during an OpenCog tutorial?).
> >> Is this proven? My intuition is that a computer could easily beat a
> >> mathematician on randomly generated problems from theorem space, but
> >> could not generate mathematically interesting theorems the way a
> >> mathematician could. In other words, I would expect the hard AGI
> >> problem to be "figure out what other mathematicians will be excited
> >> about", not "prove theorems".
> >
> > Your intuition is dead wrong based on the last decades of work in
> automated
> > theorem proving!!
> >
> > Combinatorial explosion is the problem.  The lack of effective inference
> > control, as we discussed in last night's OpenCog chat/tutorial session.
> >
> > All the most interesting achievements of automated theorem proving have
> been
> > **semi-automated**, with humans helping the AI to prune the
> > backward-chaining inference tree at the difficult places.
> >
> >>
> >> So, I don't see how one would proceed in making math-based AGI... it
> >> seems like an effective natural language interface would be needed
> >> after all, to allow the AGI to read mathematical papers, and to write
> >> its own. Otherwise, it would just be creating theorems of interest to
> >> itself, and it would be impossible to judge these as "interesting" or
> >> "uninteresting" in an objective way.
> >
> > The way to proceed would be to feed the AGI on proofs from Mizar.org ...
> >
> > But, this is certainly very hard if the AGI doesn't have any way to
> accept
> > tutoring
> >
> > Still, I imagine that via a combination of Lojban and Mizar, one could
> teach
> > an AGI theorem-proving, without needing to mess with the horrible syntax
> or
> > excessive semantic ambiguity of natural languages...
> >
> > -- Ben
> >
> > ________________________________
> > agi | Archives | Modify Your Subscription
>
>
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-- 
Ben Goertzel, PhD
CEO, Novamente LLC and Biomind LLC
Director of Research, SIAI
[EMAIL PROTECTED]

"Nothing will ever be attempted if all possible objections must be first
overcome "  - Dr Samuel Johnson



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