On Tue, Aug 5, 2008 at 10:45 AM, YKY (Yan King Yin)
<[EMAIL PROTECTED]> wrote:
> 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
>> predicates/relations/functions beyond the ones in the data are
>> allowed."
>
> Well... is "Turing complete" really that important?  I mean, most
> non-trivial KR schemes should be Turing complete.
>

I generally agree... well, except that people often invent
purposefully less-than-turing-complete formalisms in order to restrict
the search space. But for AGI purposes, this isn't as tempting.

> Also, one can "splice" new predicates into old rules, thus eliminating
> them.  So strictly speaking, new predicates do not add new content.
> But they may make machine learning easier in heuristics (just
> speculation).  Oh wait... the exception is that new predicates are
> necessary for defining recursive predicates.  So yes, predicate
> invention is necessary if resulting logic program need to contain
> recursive predicates.
>
> As for functions... ILP is complex enough with function-free FOL
> already.  Researchers usually use a "flattening" technique to
> eliminate functions.  So I don't know much about function creation.

Agreed. I think functions are mainly useful for human-readability.

>
>> So, you are not trying to create your own new probabilistic logic, you
>> are just trying to develop 1st-order bayesian networks further?
>
> Yeah, I'm trying to distribute probabilities over fuzziness, with
> first-order Bayes nets.  This is already quite complex.  And even this
> seems unable to model some subtleties of commonsense concepts.... so I
> need more thinking of it.

So, you don't think fuzziness in natural concepts reduces to probability?

>
> YKY
>
>
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> agi
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