Re: Perceptual symbol systems

From: Traveler (traveler_at_nospam.com)
Date: 08/11/04 

Date: Wed, 11 Aug 2004 10:18:29 -0400

        2In article <411a1906_1@news.athenanews.com>, "Sergio Navega"
<snavega@intelliwise.com> wrote:

>"Traveler" <traveler@nospam.com> escreveu na mensagem
>news:aodih01eokk72albi9cfh1c5v70e778vb6@4ax.com...
>> In article <4118d6a5$1_4@news.athenanews.com>, "Sergio Navega"
>> <snavega@intelliwise.com> wrote:
>>
[cut]
>> Unless you are talking about building toy robots and such, there is no
>> other solution than the neural connectionist approach.
>
>I don't see a way to support this claim, other than the suggestion
>that biological intelligences are neural. But that's not a good enough
>reason to think that *only* neural systems must be used.

It is a very simple claim to support, IMO, if only because the
interconnectedness of intelligence is so great as to be intractable to
formal means. Consider the sheer volume of sensory signals that any
advanced intelligence must process in real time. The number of
relationships (temporal correlations) which must be discovered among
the signals is astronomical. A correlation is nothing but a dependence
(a link or connection) between two events. Considering that the number
of correlations is much greater than the number of sensors, the only
solution to this problem is a connectionist approach. What other
approach can you offer that will discover and keep track of zillions
of correlations between individual events?

Now I am supposing (correct me if I am wrong) that your idea of
intelligence may have to do with text parsing and the Turing test. If
so, I can assure that text strings and Alan Turing have nothing to do
with intelligence.

[cut]
>> This is precisely it. The neural approach frees you from all the
>> constraints inherent in other approaches.
>
>Unfortunately, it adds a whole bunch of other constraints.

Such as?

[cut]
>> If you are looking for abstractions, what could be more abstract than
>> signals and signal processing? With the neural approach there is no
>> need to talk about concrete objects in the world. The type of world is
>> irrelevant, as long as it is consistent.
>
>Signals and signal processing are far from the abstractions one may
>need to understand cognition.

Funny you should say this because the brains of humans and animals use
nothing but signals and signal processing. It is the lowest level of
abstraction that is still within the domain of intelligence. But why
should one need to understand cognition to create an intelligent
machine. Again, the interconnectedness of human cognition is so high
as to be intractable to our efforts at understanding it. Even if you
could understand it (might take a trillion years), you can never keep
up with it because it is continually changing. The only thing we can
hope for is an understanding of the underlying mechanism/principles
from which it emerges.

>For one, signals are very close to
>sensory surfaces.

Not in cell assemblies like the hippocampus and the basal ganglia. But
I agree with you to a certain degree: Motor signals are removed from
the sensory layers by no more than six or seven neurons. But is it not
amazing what can be achieved with just a few layers of neurons?

>Deep inside the brain the best level of analysis
>may be different and this may have important consequences to our
>understanding of the whole process.

It is not different. It is all about temporal signal processing, as
any competent neurobiologist will tell you. Signal processing is based
on the premise that signals can be either simultaneous or sequential.
It is that simple. As amazing as it may sound, these are the only two
correlations used in the brain. The sensory layers deal with temporal
contiguity (closely succeeding signals) whereas the hippocampus
handles simultaneity and sequential correlations over multiple time
scales.

>A conventional computer can be said to be doing analogical processing,
>on a very low level of analysis. Or it can be said to be orchestrating a
>dazzling flux of electrons, on an even lower level of analysis. Or then
>it may be said that it is doing sequentially correlated logical (boolean)
>operations, on a much higher level of analysis.

As I have found in my research, logic is but a by-product of
temporal/causal signal processing (which includes motor conflict
detection) in the brain.

>If we choose to understand
>computers in that last sense, then we can conceive *another kind* of
>computer implemented by, for instance, a system that controls flows of
>water in tubes and bottles. Choosing the right level of analysis may have
>impressive consequences on what one's imagination can achieve.

You seem to be under the impression that intelligence can exist
without sensors and sensory signals. It cannot. The lowest level of
analysis (abstraction) one can get to while still remaining within the
context of intelligence is that of signal processing. This is
irrefutable, IMO.

>> >Given a set of rules and a symbolic pattern, one can manipulate it
>> >and do something useful without ever needing to know what the symbols
>> >stand for.
>>
>> And how is the intelligent system going to come up with the rules with
>> which to manipulate the symbol if it has no clue as to what the symbol
>> represents?
>
>It is not necessary to "know" what a symbol represents, provided one
>has a good set of rules to use them.

You're kidding me?

> This is not to say that I support
>symbolic (or rule-based) systems. I prefer to choose the "method" of
>processing only after I understand what needs to be done.

I can only hope that one day you will understand that what needs to be
done is temporal signal processing. Nothing else. If I were forced to
choose a single word to characterize intelligence, it would have to be
*timing*.

Louis Savain

Artificial Intelligence From the Bible:
http://users.adelphia.net/~lilavois/Seven/bible.html

Falsifiable Predictions:
http://users.adelphia.net/~lilavois/Seven/predictions.html

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