There will come a point when integrating Cyc-type assertions into
Novamente will make sense for us, and I'll be curious how useful they
turn out to be at that point....
However, my impression is that OpenCyc's rules are not extensive
enough to really add a lot to Novamente. ResearchCyc has more odds of
being helpful but can't be used for commercial purposes,
unfortunately. Still, we could integrate it with NM experimentally to
see how useful it was.
However, my view is that the integration of this sort of knowledge is
most likely to be useful to an AI system once it has achieved a
certain level of experiential intelligence, via embodied-learning
means...
ben
On 1/19/07, Stephen Reed <[EMAIL PROTECTED]> wrote:
I've been using OpenCyc as the standard ontology for my texai project.
OpenCyc contains only the very few rules needed to enable the OpenCyc
deductive inference engine operate on its OpenCyc content. On the other
hand ResearchCyc, whose licenses are available without fees for research
purposes, has a large number of rules. I have a license and can state that
my copy of RCyc has 55,794 rules out of a total of 2,689,421 non-bookkeeping
assertions. Nearly all of these rules were entered by hand at Cycorp. Here
are five at random with my comments to give you a feel for what RCyc
contains:
[this is a typical temporal relations rule]
(#$implies
(#$and
(#$startingIntervalOfThing ?TEMP-THING ?TIME-INTERVAL)
(#$startingPoint ?TEMP-THING ?TIME-POINT))
(#$endsAfterStartingOf ?TIME-INTERVAL ?TIME-POINT))
in context: #$CycTemporalTheoryMt [the Cyc term suffix Mt means microtheory
(context)]
[this is a typical spatial relations rule]
(#$implies
(#$and
(#$isa ?UNIVERSE #$UniversalSpaceRegion)
(#$partOfSpaceRegion ?REGION ?UNIVERSE)
(#$spaceRegionDifference ?COMPLEMENT ?UNIVERSE ?REGION))
(#$spaceRegionComplement ?COMPLEMENT ?REGION))
in context: #$SpatialGMt
[this is a rather specialized rule that helps define the predicate
#$eventCasualtyDataSentence]
(#$implies
(#$and
(#$isa ?PRED #$CasualtyPredicate)
(#$assertedSentence (#$relationInstanceExists ?PRED ?SUBEVENT ?COL))
(#$different ?EVENT ?SUBEVENT)
(#$subEvents ?EVENT ?SUBEVENT))
(#$eventCasualtyDataSentence ?EVENT
(#$and
(#$subEvents ?EVENT ?SUBEVENT)
(#$relationInstanceExists ?PRED ?SUBEVENT ?COL))))
in context: #$BaseKB [this is a general domain context from which almost all
other contexts inherit facts and rules]
[this is a typical rule in the naive physics domain]
(#$implies
(#$and
(#$isa ?HOLDING #$HoldingAnObject)
(#$doneBy ?HOLDING ?AGENT)
(#$objectActedOn ?HOLDING ?OBJ))
(#$holdsIn ?HOLDING (#$touches ?AGENT ?OBJ)))
in context: #$NaivePhysicsMt
[This is a rule to guide a Cyc knowledge acquisition tool. Note that this
rule represents a form of probability not seen in the other rules.]
(#$implies
(#$genls ?COL #$EnclosingSomething)
(#$keCommonQueryForTerm ?COL (#$relationAllExists #$enclosure ?COL
:WHAT)))
in context: #$BaseKB
Cheers.
-Steve
http://sf.net/projects/texai
----- Original Message ----
From: YKY (Yan King Yin) <[EMAIL PROTECTED]>
To: [email protected]
Sent: Friday, January 19, 2007 8:48:33 AM
Subject: Re: [agi] Project proposal: MindPixel 2
On 1/19/07, Benjamin Goertzel <[EMAIL PROTECTED]> wrote:
> Well YKY, I don't feel like rehashing these ancient arguments on this
list!!
>
> Others are welcome to do so, if they wish... ;-)
>
> You are welcome to repeat the mistakes of the past if you like, but I
> frankly consider it a waste of effort.
>
> What you have not explained is how what you are doing is fundamentally
> different from what has been tried N times in the past -- by larger,
> better-funded teams with more expertise in mathematical logic...
Well I think people gave up on logic-based AI (GOFAI if you will) in the 80s
because of newer techniques such as neural networks and statistical learning
methods. They were not necessarily aware of what exactly was the cause of
failure. If they did, they would have tackled it.
For the type of common sense reasoner I described, we need a *massive*
number of rules. You can either acquire these rule via machine learning or
direct encoding. Machine learning of such rules is possible, but the area
of research is kind of immature. OTOH there has not been a massive project
to collect such rules by hand. So that explains why my type of system has
not been tried before.
My system is conceptually very close to Cyc, but the difference is that Cyc
only contains ground facts and rely on special predicates (eg $isa, $genl)
to do the reasoning. My project may be the first to openly collect facts as
well as rules.
I guess Novamente or NARS can benefit by importing these rules, if the
format is right?
YKY This list is sponsored by AGIRI: http://www.agiri.org/email
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