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
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>> >>
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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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>>
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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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