Sergio:When we describe our world, we arbitrarily select the *granularity* of
our description.
(A) "The buttler is the assasin. He was at the scene, and he has a motive."
That's a very coarse granularity, but it is already a causal set.
Still, we can already take action. We can arrest the buttler and find more
facts.
(B) "The crime took place at 7:30."
(C) "The buttler left the scene at 7:29."
And we can draw a conclusion:
(D) "The buttler was not at the scene at the time of the crime.
We have now a better description, a finer granularity.
But what does it mean to "draw a conclusion?"
It means to *bind* or *associate* B and C to generate D.
This is a logical step, and requires a mathematical logic operating on the
causal set.
Sergio,
Gotcha,
It’s hard to get examples of problemsolving out of you & others – but as soon
as you do, one can get somewhere.
You’re talking here about an example of an extremely broad class of real-world
problemsolving – detection. Scientific theorising – incl. say when s.o. works
out the cause of a disease – comes under detection. In detection, you have to
work from evidence to detect hidden causes.
Real world problemsolving, incl, detection, has absolutely nothing to do with
logic. To suggest otherwise is naive.
Real world problemsolving requires an extremely complex imaginative scenic
knowledge of how actors and actions unfold in given scenes over time - a movie
knowledge, not the sentential knowledge of language and logic.
In this case, you have to know about people moving in and out of rooms, and
(perhaps) how weapons are fired, and what kinds of weapons have what effects
and much else – and all of this is imaginative – image-based.
It is a total illusion to think that logic is involved - logic and language
are merely sticking labels on the images - putting labels to
movie/diagrammatic reasoning. Nothing happens without the movie/diagrammatic
reasoning.
You may only be aware consciously of reasoning with words and letters, but
closer examination will show that massive imaginative reasoning underlies the
surface.
So if I say to you:
“ok sure, he left the room at 7.29, but he could have gone round the back and
fired in through the window at 7.30”
where is your logic going to get you? How are A B C and D going to handle that?
You have to be able to **imagine** the physical connection across a complex
scene between evidence and cause - here between s.o. moving and running
round the rooms, the house, the window, the position of the victim and so on –
in order to agree or disagree with this argument. You have to **imaginatively
reconstruct the scenes** ..
“No that would have taken too long, surely... or he just might have managed it
... er why don’t we go and check?”
You do indeed DRAW conclusions – by drawing lines across imaginative scenes
between evidence and hypothetical causes – to see for example whether s.o.
could have managed to run round, and whether s.o. outside the window could
indeed have managed to hit the victim.
The same principles apply to ALL scientific reasoning, ALL technological
reasoning, - ALL real world reasoning.
Your causal sets are a total fantasy when applied to **any** real world
problem, (including BTW real world vision).
An examination of the evidence of how scientists and others (including criminal
detectives reason) will show that none of them use logic to DRAW conclusions.
No one employs logicians for real world reasoning.
An examination of all logical reasoning – by logicians – will also show no
results that were of any direct use in real world reasoning. Logic produces
only the most trivial of results. “Was the victim a man?” “Then he is mortal.”
Thankyou and goodnight.
Logic is blind – it cannot see any evidence. It cannot tell us anything new
about the real world. Repeat: nothing new.
Logic can only be used to explore the ramifications of a given set of known
relationships between a given set of letters. It takes imaginative reasoning
to make the connection between reasoning about artificial A’s, B’s, C’s and D’s
– and physical events. Logic is utterly dependent on imaginative reasoning. And
in real world reasoning, as distinct from logic, you can’t be sure what
relationships do obtain. [“You say he was murdered – but it could have been a
pre-arranged suicide”).
So the only conclusion about the applicability of causal sets to real world
reasoning, Sergio is --
back to the DRAWING board -
of the imagination.
From: Sergio Pissanetzky
Sent: Saturday, September 01, 2012 3:56 PM
To: AGI
Subject: [agi] Granularity
AGI,
I don't recall having explained granularity on this blog before. My neglect has
caused
misunderstandings. So here it is.
When we describe our world, we arbitrarily select the *granularity* of our
description.
(A) "The buttler is the assasin. He was at the scene, and he has a motive."
That's a very coarse granularity, but it is already a causal set.
Still, we can already take action. We can arrest the buttler and find more
facts.
(B) "The crime took place at 7:30."
(C) "The buttler left the scene at 7:29."
And we can draw a conclusion:
(D) "The buttler was not at the scene at the time of the crime.
We have now a better description, a finer granularity.
But what does it mean to "draw a conclusion?"
It means to *bind* or *associate* B and C to generate D.
This is a logical step, and requires a mathematical logic operating on the
causal set.
The logic removes uncertainty from the causal set and creates structure.
The set {B, C} is uncertain. We know B and C, but we ask "so what?"
To reach D we have to remove the uncertainty.
Removing uncertainty is easy for our brains.
We don't even notice it happened because we are not aware of it happening.
It is unconscious, and our brains do it all the time.
You the reader can continue the excercise.
Every bit of information we acquire is followed by a "remove uncertainty" step.
Our brains are constantly removing uncertainty.
AGI will never work unless we learn how to "remove uncertainty" on a computer.
No adaptive system will work unless we learn how to "remove uncertainty" on a
computer.
Have courage, don't leave the uncertainty there.
I must have tired everyone by saying entropy all the time. But entropy is just
a measure of uncertainty. If someone is 6 feet tall, I must use "feet" to say
that.
Sergio
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