Ben, BTW, you may try inviting Stephen Muggleton to AGI'09. He
actually talked to me a few times despite that I knew very little
about ILP at that time. According to the wikipedia page he is
currently working on an `artificial scientist' .
http://en.wikipedia.org/wiki/Stephen_Muggleton
YKY
On 8/5/08, Ben Goertzel [EMAIL PROTECTED] wrote:
Yes, but in PLN/ OpenCogPrime backward chaining *can* create hypothetical
logical relationships and then seek to estimate their truth values
See this page
http://opencog.org/wiki/OpenCogPrime:IntegrativeInference
and the five pages linked to
On Tue, Aug 5, 2008 at 7:45 AM, YKY (Yan King Yin)
[EMAIL PROTECTED] wrote:
Can you create hypotheses that contain variables? If yes, what you're doing
is essentially ILP. If not, then your version is a kind of propositional
learning, like ID3, and is inadequate for AGI.
Well, NARS has
On 8/5/08, Abram Demski [EMAIL PROTECTED] wrote:
As I understand it, FOL is only Turing complete when
predicates/relations/functions beyond the ones in the data are
allowed. Would PLN naturally invent predicates, or would it need to be
told to specifically? Is this what concept creation does?
On 8/5/08, Abram Demski [EMAIL PROTECTED] wrote:
Prolog (and logic programming) is Turing complete, but FOL is not a
programming language so I'm not sure.
You are right, I should have said FOL is turing complete within the
right inference system [such as Prolog], but only when
On 8/6/08, Jim Bromer [EMAIL PROTECTED] wrote:
You made some remarks, (I did not keep a record of them), that sounds
similar to some of the problems of conceptual complexity (or
complicatedness) that I am interested in. Can you describe something
of what you are working on in a little more
On Tue, Aug 5, 2008 at 3:24 PM, YKY (Yan King Yin)
[EMAIL PROTECTED] wrote:
I'm writing a paper about my probabilistic-fuzzy logic that should be
fairly easy to understand. But I got stuck on the fuzzy concept
problem as you can see.
To distribute probabilities over fuzziness means: each
I mentioned earlier that I'd forward a private email I'd previously sent to
YKY, on the topic of probabilistic inductive logic programming.
Here is is.
As noted there, my impression is that PILP could be implemented within
OpenCog's PLN backward chainer (currently being ported to OpenCog by Joel
On Mon, Aug 4, 2008 at 6:10 PM, YKY (Yan King Yin)
[EMAIL PROTECTED] wrote:
On 8/5/08, Ben Goertzel [EMAIL PROTECTED] wrote:
As noted there, my impression is that PILP could be implemented within
OpenCog's PLN backward chainer (currently being ported to OpenCog by Joel
Pitt, from the
As I understand it, FOL is only Turing complete when
predicates/relations/functions beyond the ones in the data are
allowed. Would PLN naturally invent predicates, or would it need to be
told to specifically? Is this what concept creation does? More
concretely: if I gave PLN a series of data, and
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