On Tue, Jun 3, 2008 at 3:46 PM, YKY (Yan King Yin)
<[EMAIL PROTECTED]> wrote:
> Hi Ben,
>
> Note that I did not pick FOL as my starting point because I wanted to
> go against you, or be a troublemaker.  I chose it because that's what
> the textbooks I read were using.  There is nothing personal here.
> It's just like Chinese being my first language because I was born in
> China.  I don't speak bad English just to sound different.
>
> I think the differences in our approaches are equally superficial.  I
> don't think there is a compelling reason why your formalism is
> superior (or inferior, for that matter).

I disagree ... it's not a matter of differing formalisms.

There are a number of deep issues you have to confront if you want
to make an AGI based on uncertain logic, e.g.

1) representing uncertainties in a way that leads to tractable, meaningful
logical manipulations.  Indefinite probabilities achieve this.  I'm not saying
they're the only way to achieve this, but I'll argue that single-number,
Walley-interval, fuzzy, or full-pdf approaches are not adequate for various
reasons.

2) using inference rules that lead to relatively high-confidence uncertainty
propagation.  For instance term logic deduction is better for uncertain
inference than modus ponens deduction, as detailed analysis reveals

3) propagating uncertainties meaningfully through abstract logical
formulae involving nested quantifiers (we do this in a special way in PLN
using third-order probabilities; I have not seen any other conceptually
satisfactory solution)

4) most critically perhaps, using uncertain truth values within inference
control to help pare down the combinatorial explosion


How these questions are answered matters a LOT, and my colleagues
and I spent years working on this stuff.  It's not a matter of converting
between equivalent formalisms.

-- Ben G


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agi
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