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."
There are none. Logic cannot observe the world. Logic has never discovered a
single new fact about the world. Logic can only work out ramifications of
existing observations/facts. No real world reasoner - scientist,
technologist - et al uses logic.
As I more or less indicated below, your logical propositions piggybacked on
my imaginative observations.
Logic, like justice, is literally blind.
--------------------------------------------------
From: "Ben Goertzel" <[email protected]>
Sent: Saturday, June 16, 2012 11:53 PM
To: "AGI" <[email protected]>
Subject: Re: [agi] Real World Reasoning
To know
whether they could have missed each other you really do have to visualise
the clinic and the possible crowds and the individual figures - and
"figure
out" whether they could be physically apart enough not to see each other.
Reasoning here depends on the brain's imaginative capacity to move
figures
around the world's scenes/stages and check whether they fit together or
not.
Checking whether logical symbols match each other isn't going to help
you,
and is a fundamentally secondary operation.
No, what you describe is just one possible strategy for solving the
problem.
OpenCog also has some code for this sort of simulation modeling, but it's
not always needed...
If asked whether two folks in a doctor's clinic at around the same time
are
likely to bump into each other, I can certainly answer the question
without
visualizing the clinic.
If someone asked me that question "Jane and Sally were at a certain
doctor's
clinic at around the same time; do you think they bumped into each
other?",
I wouldn't necessarily ask the questioner about the specific geometry
of the clinic,
I might just ask something general like "How big is the clinic? How big
is the
waiting area? How many people tend to be there at once?"
Based on this general information, I could then reason logically about the
odds
that Jane and Sally bumped into each other. The chain of reasoning might
go something like
(A and B) implies C
where
A)
Two people in a big crowded space are unlikely to notice each other
B)
The doctor's office is a big crowded space, according to what I've just
been told
C)
Jane and Sally probably didn't notice each other when they were in the
doctor's office
...
This is **uncertain logical reasoning** applied to commonsense knowledge.
At some point in the history of the mind doing this reasoning, the
proposition
(A) was probably learned from experience [though it's possible to learn
such
things via language instead].... However, just because I learned (A) via
visual, embodied experience at some point in my past, doesn't prevent me
from using (A) in the future in chains of logical reasoning where I have
no idea
what the big crowded space in question looks like.
This is part of the power of logical reasoning: it lets us draw
conclusions about cases
where we **lack** the concrete sensory information or episodic memory to
use more direct methods.
There's no contradiction between visual observation, "mind's eye"
simulation,
and logical reasoning. These mental processes all need to work together.
There's also no contradiction between logical reasoning, as a description
of what minds do sometimes, and neural network modeling as a way of
describing brains. There are clear connections between logical inference
rules and neural net dynamics (e.g. Hebbian learning between neuronal
groups and uncertain term logic deduction). Neural nets can implement
logical inference along with other cognitive methods, though in OpenCog
we have not currently chosen neural nets as our implementation tool.
It seems you may be unaware of the unconscious uncertain logical
reasoning your mind
continually does. But this deficit in your own introspective habits
or capability,
while unfortunate for you, shouldn't be taken as a constraint for others'
AGI
development work....
-- Ben G
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