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
>
>
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> 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
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