It's not always a problem in principle, but I'd need to think about the
specific case more carefully...
On Mon, Sep 22, 2008 at 4:56 PM, Abram Demski <[EMAIL PROTECTED]> wrote:
> Possibly, but how would you mix infinite-order probabilities with
> regular probabilities?
>
> -Abram
>
> On Mon, Sep 22, 2008 at 1:28 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote:
> >
> > The {A} statements are consistent with NARS, but the existing NARS
> inference
> > rules don't use these statements...
> >
> > A related train of thought has occurred to me...
> >
> > In PLN we explicitly have both intensional and extensional inheritance
> links
> > (though with semantics nonidentical to that used in NARS, and
> fundamentally
> > probabilistic in nature) ... so the "probabilistic quasi-NARS" logic
> you're
> > describing could potentially be used as a sort of "NARS on top of PLN"
> ...
> >
> > I'm not sure how useful such a thing is, but it might be interesting...
> >
> > ben
> >
> >
> >
> > On Mon, Sep 22, 2008 at 12:18 PM, Abram Demski <[EMAIL PROTECTED]>
> > wrote:
> >>
> >> Sure, but it is a consistent extension; {A}-statements have a strongly
> >> NARS-like semantics, so we know they won't just mess everything up.
> >>
> >> On Mon, Sep 22, 2008 at 11:31 AM, Ben Goertzel <[EMAIL PROTECTED]>
> wrote:
> >> >
> >> > Of course ... but then you are not doing NARS inference anymore...
> >> >
> >> > On Mon, Sep 22, 2008 at 8:25 AM, Abram Demski <[EMAIL PROTECTED]>
> >> > wrote:
> >> >>
> >> >> It would be possible to get what you want in the setting, by allowing
> >> >> some probabilistic manipulations not done in NARS. The node
> >> >> probability you want in this case could be simulated by talking about
> >> >> the probability distribution of sentences of the form "X is the
> author
> >> >> of a book". We can give this a low prior probability. Since the
> system
> >> >> manipulates likelihoods, it won't notice; but if we manipulate
> >> >> probabilities, it would.
> >> >>
> >> >> Perhaps a more satisfying answer would be to introduce a new operator
> >> >> into the system, {A}, that simulates the node probability; or more
> >> >> specifically, it represents the average truth-value distribution of
> >> >> statements that have A on one side or the other. So, it has a 'par'
> >> >> value just like inheritance statements do. If there was evidence for
> a
> >> >> low par, there would be an effect in the direction you want. (It
> might
> >> >> be way too small, though?)
> >> >>
> >> >> --Abram
> >> >>
> >> >> On Sun, Sep 21, 2008 at 10:46 PM, Ben Goertzel <[EMAIL PROTECTED]>
> >> >> wrote:
> >> >> >
> >> >> >
> >> >> > On Sun, Sep 21, 2008 at 10:43 PM, Abram Demski
> >> >> > <[EMAIL PROTECTED]>
> >> >> > wrote:
> >> >> >>
> >> >> >> The calculation in which I sum up a bunch of pairs is equivalent
> to
> >> >> >> doing NARS induction + abduction with a final big revision at the
> >> >> >> end
> >> >> >> to combine all the accumulated evidence. But, like I said, I need
> to
> >> >> >> provide a more explicit justification of that calculation...
> >> >> >
> >> >> > As an example inference, consider
> >> >> >
> >> >> > Ben is an author of a book on AGI <tv1>
> >> >> > This dude is an author of a book on AGI <tv2>
> >> >> > |-
> >> >> > This dude is Ben <tv3>
> >> >> >
> >> >> > versus
> >> >> >
> >> >> > Ben is odd <tv1>
> >> >> > This dude is odd <tv2>
> >> >> > |-
> >> >> > This dude is Ben <tv4>
> >> >> >
> >> >> > (Here each of the English statements is a shorthand for a logical
> >> >> > relationship that in the AI systems in question is expressed in a
> >> >> > formal
> >> >> > structure; and the notations like <tv1> indicate uncertain truth
> >> >> > values
> >> >> > attached to logical relationships, In both NARS and PLN, uncertain
> >> >> > truth
> >> >> > values have multiple components, including a "strength" value that
> >> >> > denotes a
> >> >> > frequency, and other values denoting confidence measures. However,
> >> >> > the
> >> >> > semantics of the strength values in NARS and PLN are not
> identical.)
> >> >> >
> >> >> > Doing these two inferences in NARS you will get
> >> >> >
> >> >> > tv3.strength = tv4.strength
> >> >> >
> >> >> > whereas in PLN you will not, you will get
> >> >> >
> >> >> > tv3.strength >> tv4.strength
> >> >> >
> >> >> > The difference between the two inference results in the PLN case
> >> >> > results
> >> >> > from the fact that
> >> >> >
> >> >> > P(author of book on AGI) << P(odd)
> >> >> >
> >> >> > and the fact that PLN uses Bayes rule as part of its approach to
> >> >> > these
> >> >> > inferences.
> >> >> >
> >> >> > So, the question is, in your probabilistic variant of NARS, do you
> >> >> > get
> >> >> >
> >> >> > tv3.strength = tv4.strength
> >> >> >
> >> >> > in this case, and if so, why?
> >> >> >
> >> >> > thx
> >> >> > ben
> >> >> > ________________________________
> >> >> > agi | Archives | Modify Your Subscription
> >> >>
> >> >>
> >> >> -------------------------------------------
> >> >> agi
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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
> >> >
> >> >
> >> > ________________________________
> >> > agi | Archives | Modify Your Subscription
> >>
> >>
> >> -------------------------------------------
> >> agi
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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
> >
> >
> > ________________________________
> > 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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