On Sun, Jun 17, 2012 at 6:43 PM, Ben Goertzel <[email protected]> wrote
If you knew more about real-world uses of logic systems, you would
know that **inference control** doesn't have to be done by logical
mechanisms.... The choice of which premises to explore in a logical
inference chain, can be done by lots of methods besides logic. That
is, in a real-world reasoning context, logical inference will
generally be nudged and guided in the right direction by non-logical
methods...
----------------------------------------------------------
But, the fact that many of these actions can be said to be logical
decisions, given the evidence that the program is working with at the time,
is not just a coincidence.

The original theory that logic was the highest form of reasoning, the kind
of reasoning that scientists do, looks like it is pretty much a thing of
the past now.  However, the fact that our usual methods of reasoning can be
described by *form* shows that this method of logical reasoning or
reasoning by form is not something that can be dismissed.

When we try to anticipate something that is too far out in the future our
predictions about the event can be pretty awful.  (People who talk about
using "prediction" in AGI are people who have never actually written out
their "predictions" to see if they can actually use predictions in life.  I
think the term "prediction" in AGI just refers to something that is
known.)  If our predictions about what, precisely, is going to happen
during the next month is as bad as they usually are, it should not be much
of a surprise to discover that our *forms* or formal categorical methods
that an AGI program could use to deal with might happen in the next
month might be a little off as well.

However, to say that a reasonable method that is used to "generally nudge
and guide logical inference in the right direction," are not the products
of logic is a little dubious.  An educated guess is one that is based on
logical use of insight - although the logic may be hidden.

Jim BRomer



On Sun, Jun 17, 2012 at 6:43 PM, Ben Goertzel <[email protected]> wrote:

> On Sun, Jun 17, 2012 at 2:11 AM, Mike Tintner <[email protected]>
> wrote:
> > How do you get to A): ?
> >
> >
> > A)
> > Two people in a big crowded space are unlikely to notice each other
> >
> > from:
> >
> > "Sue and Jane were both at the clinic at 4.00 - did they see each other?"
> >
> > How do you know to ask questions about the clinic and Sue and Jane and
> > seeing?
> >
> > Please outline the **logical** principles  - esp. those you think
> existed in
> > your head about "crowded spaces", "people" and "seeing."
>
>
> If you knew more about real-world uses of logic systems, you would
> know that **inference control** doesn't have to be done by logical
> mechanisms....  The choice of which premises to explore in a logical
> inference chain, can be done by lots of methods besides logic.  That
> is, in a real-world reasoning context, logical inference will
> generally be nudged and guided in the right direction by non-logical
> methods...
>
> In this case, a simple lookup into episodic memory would probably do
> the trick...
>
> If the system's memory contained many cases of people in the same
> place who did see each other ,and also many cases of people in the
> same place who did not see each other...
>
> THEN, a supervised learning method like MOSES could be automatically
> launched inside the system, to learn which patterns distinguish the
> "did see" cases from the "didn't see" cases...
>
> One of these patterns might be: if the people were in a place that is
> both large and crowded, they often did not see each other...
>
> This pattern, derived via inductive pattern-recognition from a set of
> remembered instances, would then guide logical inference...
>
> Note that a mind can try out 10000s of possible logical inferences
> very quickly, in parallel, until it finds one that seems to yield
> useful information about the subject at hand...
>
> Using an internal simulation-world, as you suggest, would be one
> possible way to solve the problem you mention.  However, there are
> many other ways a mind could solve it, and I've described one:
> uncertain logical inference, with inference control guided by
> supervised learning acting on declarative episodic memory...
>
> -- Ben G
>



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