On 9/1/08, Benjamin Johnston <[EMAIL PROTECTED]> wrote:

Thanks for your comments =)

> --------------------------
> 1. Why just P,Z and B?
> Three mechanisms seems somewhat arbitrary - I think you need to make a very
> compelling case for why there are three and only three mechanisms.
>
> Or, more interestingly, I wonder if you could generalize the reasoning
> framework so that every statement has a potentially unlimited number of
> measures:

This has been proposed before, and the problem, as pointed out by
[Simon Parsons 2001], is that we need to specify an exponential number
of ways of how the different TV types interact / interconvert.

Also, we want to create a new TV type, such as "roughness" (as in
rough sets), we may be able to build it on top of a base logic such as
BPZ.  In fact, I suspect that the "base logic" in the human brain does
not include probabilistic logic, which is why many lay people fail at
Bayesian reasoning tasks, but it also explains why human Bayesian
experts can master this art despite that their brains do not have
hard-wired probabilistic logic, either.

So it seems to be a balance between
1.  value-added
2.  simplicity (and thus computational efficiency)
3.  coverage of uncertain phenomena

> --------------------------
> 2. Why must the 12 combinations on page 19 be analysed separately?
> Could these 12 cases be abstracted into some more general principle? Is
> there some way of rethinking the reasoning mechanisms so that the 12 cases
> don't seem to include arbitrary choices (e.g., "Convert the B variable to a
> Z variable - but this is disallowed. We may convert the B variable
> to a P(Z) variable and then invoke Case #8.").

Yes, the 12 cases can be abstracted into 1 general mechanism, where
everything is P(Z), ie "P distributed over Z".  But this logic seems
to be slower than B, P, Z separately.  I will try to elaborate this in
the next version....

> --------------------------
> 3. How would you deal with context?
> Something like "the water is hot" can mean different things depending on
> whether you're talking about: making a cup of coffee, washing clothes, a
> bathtub, a competitive swimming pool, or a glass of cool water without ice
> on a hot day. Modifiers like "very" and "extremely" are similarly context
> dependent, and gender, in particular, can have vastly different meanings
> depending on context (even though we as humans are able to immediately
> recognize what context is meant in most cases): social gender, genetic
> gender, physical gender, gender identity, sexual gender, ...

I have some vague ideas of how to deal with contexts (as a multitude
of rules competing for the highest confidence).  I will try to
formulate that better.

> --------------------------
> You present a "taxonomy of ignorance" (Figure 1) and assume it is
> self-evident from the taxonomy that P and Z are sufficient. I certainly do
> not find it to be self-evident: I don't see how the diagram supports your
> argument.

Right, it was just a sleigh-of-hand =)

I guess the only argument I can make is to show that a lot of examples
in everyday uncertainty can be reduced to BPZ.  That's rather time
consuming though.

> Even though you apologize for not being politically correct, I still think
> you should find better examples that do not have the potential to offend
> readers. Rather than saying hermaphrodites are degree 0.6 typical human(?),
> I'm sure you could find a simple and obvious example that addresses human
> emotions that is less insensitive.

I just chose the first example that comes to mind.  Let's see if I can
find better ones... but this is also very time-consuming... =(

> It doesn't look very professional when you cite Wikipedia.

Well, the whole paper is more like a tutorial, with a conversational
style.  If I submit to AGI'09 I'd revise it and make it more like an
academic journal paper. =)

YKY


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agi
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