On 9/2/08, Ben Goertzel <[EMAIL PROTECTED]> wrote:
>
> About indefinite/imprecise probabilities, you dismiss them as
> overcomplicated, but you don't address the reason they were introduced in the
> first place: In essence, to allow a rationally manipulable NARS-like
> confidence measure that works nicely w/ probabilistic inference and has a
> probabilistic justification.
NARS confidence is.... not exactly derived from probability, but is
compatible with probability. If you have a better measure of
confidence, that's of course a good thing, but I don't see why 2nd
order P is needed for doing this.
> What is the semantics of your confidence values? Pei's confidence values
> have a clear nonprobabilistic semantics, and PLN's have a clear semantics in
> terms of indefinite probabilities. If you mix NARS confidences with
> probabilistic inferences you have something semantically confused...
Let me have some thinking on it... right now it seems to me that NARS
confidence and probability are orthogonal...
> Also, in your example
>
> A = "Jim had sex with 1000 women"
>
> B = "Jim had cybersex with 1000 women"
>
> A1 = "Jim had sex with woman_1"
>
> B1 = "Jim had cybersex with woman_1"
>
> you seem to assume that in a probabilistic approach
>
> (Inheritance B A).strength =
>
> ( (Inheritance B1 A1).strength)^1000
The "implication" (or inheritance in your parlance)
Jim has cybersex --> Jim has sex
is NOT regarded as probabilistic in my view, but it's fuzzy.
If you view that inheritance as probabilistic, there *may* be some
semantic problems, but such problems may be gotten around by clever
tricks -- though I don't know how.
> but in a PLN approach this could be avoided by looking at
>
> IntensionalInheritance B A
>
> rather than extensional inheritance..
>
> Note that PLN's intensional inheritance incorporates some fuzziness
> but within a probabilistic framework... we have
>
> IntensionalInheritance B A =
>
> ExtensionalInheritance ( Prop(B) Prop(A) )
>
> where Prop(X) is the fuzzy set of properties of X (defined in a specific
> way within PLN)
Yes, you seem to have solved the problem in an alternative way.
Though I'm still unclear about your definition of extensional vs
intensional. It seems to be analogous to the definition in thermal
physics. We have at least 4 definitions of it: from ILP, NARS, Judea
Pearl, Ben G. =)
> So fuzzy logic per se is not the only way to handle situations like this
> in a semantically natural, commonsensical way.. there are many ways
> consistent w probability theory I'm sure, including the PLN way...
That's true. I concur that. But... we need to consider computational
constraints... there may be a need to prefer simpler logics...
> All in all, my sense is that you want to graft together some standard stuff
> with relatively minor tweaks ... and I am left wondering why you think that
> such
> a relatively straightforward integration of small variations on well-known
> stuff is
> going to give results more exciting than those already in the literature....
> Maybe
> there is a good reason, but it didn't seem to be made clear in the paper...
Some things are new in my logic: fuzzy logic used to be rather
difficult to apply because the inference algorithms are complex.
Also, I kind of touched up fuzzy theory to make it semantically more
"precise" (?)
YKY
-------------------------------------------
agi
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