PM,

One of my favorite subjects...

variables appear to have value, significance, and dimensionality.

You have chosen to restrict your thinking to binary values, while ignoring
significance and dimensionality.

You proposition could have a value other than T or F, and every proposition
almost certainly has a value somewhere between T and F, expressing the
believed probability of it being true, based on a finite set of
observations.

Further, propositions have significance. For example, you may precisely
know the values of various independent variables, but be unsure of how to
manipulate them to compute an interesting parameter. There is a BIG
difference between probabilities of:
0.5       Believed to be 50:50 without much evidence.
0.50     Believed to be 50:50 based on hundreds of observations.
0.500   Believed to be 50:50 based on careful analysis and confirmed by
hundreds of observations.

Then there is the most interesting parameter of all - dimensionality, which
I believe guides the construction of our brains. This tells us what sort of
measure this is, e.g. position, intensity, probability, confidence, etc.,
etc.

As for representational non-existence, how can you represent that which you
don't know anything about, including its very existence? We do this all the
time, and it takes no space. It just isn't there. It has no value, no
significance, and no dimensionality, and hence it also has no existence.

So, in summary, your conundrum arises from "trimming" the problem WAY below
the minimum needed to understand it.

Steve
=============
On Thu, Sep 18, 2014 at 11:10 AM, Piaget Modeler via AGI <[email protected]>
wrote:

> How have knowledge representations dealt with the absence of a
> proposition?
>
> Suppose there is a knowledge base KB containing a proposition
>
> P
>
> We can represent P being false as
>
> (not P)
>
> But how do you represesent the fact that neither P nor (not P)  are in the
> KB?
>
> Kindly advise.
>
> ~PM
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